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Libya - Supporting Electricity Sector Reform (P154606)
Contract No. 7181909 - Task D: Strategic Plan for Renewable Energy Development
Least Cost Expansion Plan (LCEP) - Up-dated Final Report Energy Mix and Renewable Resource Assessment 12th December 2017
Client:
The World Bank
1818 H Street, N.W.
Washington, DC 20433
Consultant:
GOPA-International Energy Consultants GmbH
Justus-von-Liebig-Str. 1, 61352 Bad Homburg, Germany
Phone: +49-6172-1791-800; Fax: +49-6172-944 95 20
eMail: info@gopa-intec.de; www.gopa-intec.de
Suntrace GmbH
Grosse Elbstrasse 145c, 22767 Hamburg, Germany
Phone: +49-40-767 96 38 0; Fax: +49-40-767 96 38 20
www.suntrace.de
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Libya SPREL – LCEP Final Report
LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx
Table of Contents Page
1. Introduction 4
2. Background 6
3. Approach and Methodology 7
4. Load and Supply Characteristics 8
4.1 Load Characteristics and Demand Projections 8
4.2 Supply Projections – Baseline of Conventional Power 9
5. Areas for the LCEP 12
6. Conditions, Constrains and Inputs into LCEP 15
6.1 The LCEP Model 15
6.1.1 The LCEP Target Function 16
6.1.2 Basis Years 17
6.1.3 Solution Variables 17
6.1.4 Capacity Credit 18
6.1.5 Brief Notes on Modelling Approach 19
6.2 Inputs to the model 19
6.2.1 Demand Growth 19
6.2.2 Existing and Pipeline Projects (Conventional) 19
6.2.3 RE Technology Configurations and Sites 19
6.2.4 RE Technology Costs and Values over Time 20
6.2.5 Exogenous Assumptions – Fuel Price 23
6.2.6 Technology Configurations and Costs for New Conventional 23
6.3 Side constraints 24
6.3.1 Satisfaction of Demand 25
6.3.2 Satisfaction of Peak Load Plus Reserve Capacity 25
6.3.3 Minimum Load Of Conventional Power Plants 25
6.3.4 Short Term and Long Term and Maximum RE Capacity 25
6.3.5 Year of Commissioning for New Conventional and Renewable
Configurations 27
7. Scenarios 28
8. Sensitivities 31
9. Results of Scenario and Sensitivities 32
9.1 Scenario 4 (Sc4), No RE 32
9.2 Scenario 2 (Sc2), Unlimited RE 32
9.3 Scenario 3c (Sc3c), Reference Case 33
9.4 Sensitivities 35
9.5 Summary of Results 39
10. LCEP Follow-up 42
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Table of Contents Page
List of Annexes
Annex I - Solar and Wind Resource
Annex II - Grid Connection Aspects
Annex III - Potential Areas and Sites
Annex IV – Information Collected
Annex V – Performance of Conventional Plants
Annex VI – Cost of Capital Assumptions
List of Tables
Table 4-1: Power plants for LCEP model – Worst case (Source: Task A)
Table 4-2: Power plants for LCEP model – Best case (Source: Task A)
Table 5-1: Technology configuration for LCEP
Table 6-1: Main performance, cost and technical values for the RE technology configurations
Table 6-2: Projection of LNG prices until 2030 (Source : Task B)
Table 6-3: Summary of fuel cost projections for the LCEP
Table 6-4: CAPEX and OPEX estimations for new non-RE power plants (Source)
Table 6-5: Short-term capacity restrictions for the LCEP areas in MW
Table 7-1: Summary of scenarios
Table 8-1: Summary of sensitivities
Table 9-1: Summary of scenario results
Table 9-2: Summary of sensitivity results
List of Figures
Figure 4-1: Exemplary daily profiles of monthly average load curves (MW)
Figure 4-2: Scenarios for electricity consumption until 2030 (Task A)
Figure 4-3: Scenarios of GECOL’s generation and T&D (Task A)
Figure 5-1: Preselected areas for the LCEP
Figure 6-1: LCEP Model
Figure 6-2: Long-term expansion limits of RE capacity for the LCEP
Figure 9-1: Scenario 4, reflecting unlimited RE implementation of 12.35 GW until 2030
Figure 9-2: Newly installed capacity for the Reference Case
Figure 9-3: Reference case: Produced energy until 2030
Figure 9-4: Cost comparison showing savings in Sc3c (reference) in compared to Sc4 (No RE)
Figure 9-5: Sensitivity 1, no constrain for wind power
Figure 9-6: Sensitivity 1, no constrain for wind power, produced energy until 2030
Figure 9-7: Sensitivity 2, WACC for CSP lowered to 4%,
Figure 9-8: Sensitivity 2, WACC for CSP lowered to 4%, produced energy until 2030
Figure 9-9: Sensitivity 3, Fuel price variation
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Abbreviations
CAPEX Capital Expenditures
CCGT Combined Cycle Gas Turbine
CRS/CR Central Receiver System
CSP Concentrating Solar Power
DNI Direct Normal Irradiation
DSG Direct Steam Generation
ENTSO European Network of Transmission System Operators
ESS Energy Storage System
FLH Full Load Hours
GECOL General Electric Company of Libya
GHI Global Horizontal Irradiation
GI Global Irradiation
GT Gas Turbine
HFO Heavy Fuel Oil
HRSG Heat Recovery Steam Generator
HTF Heat Transfer Fluid
IDC Interest During Construction
IEC International Electro-chemical Commission
IGBT Insulated Gate Bipolar Transistor
IPP Independent Power Producer
IRR Internal Rate of Return
ISCC Integrated Solar Combined Cycle
ITRPV International Technology Roadmap for Photovoltaic
LCEP Least Cost Expansion Plan
LCoE Levelized Cost of Electricity
LDS Long-Duration Energy Storage
LFO Light Fuel Oil
LID Light Induced Degradation
LLJ Low Level Jet
LVRT Low Voltage Ride Through
OPEX Operational Expenditures
PID Potential Induced Degradation
PPA Power Purchase Agreement
PSP Private Sector Participation
PT Parabolic Trough
PV Photovoltaics
RE Renewable Energies
REAOL Renewable Energy Authority of Libya
SCGT Simple Cycle Gas Turbine
SM Solar Multiple
STATCOM Static Compensators
SPREL Strategic Plan for Renewable Energies in Libya
TES Thermal Energy Storage
TMY Typical Meteorological Year
TSC Thyristor Switched Capacitors
WACC Weighted Average Capital Cost
WB World Bank
WTG Wind Turbine Generator
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1. Introduction
The Least Cost Expansion Plan (the LCEP) analysis is the first step towards the preparation of a Stra-
tegic Plan for Renewable Energies in Libya (the SPREL). This report describes the methods, assump-
tions, processes, inputs and outcomes undertaken and found by the Consultant in order to optimize a
mix of Renewable Energies (RE) for Libya until 2030 as part of Task D, Strategic Plan for Renewable
Energy Development, mandated by the World Bank.
In the present situation Libya power generation park is not sufficient to cover peak demand for differ-
ent reasons including the lack of resources/fuel, missing spare parts, maintenance or damaged infra-
structure. However, the conventional power projects, either contracted or under development, which
have been put on hold due to the current political situation could, if implemented, cover the demand in
the future. In principle, renewable energies (RE) do not have to step in to close supply gaps but eco-
nomic perspective, energy security and long-term perspective are at least three important arguments
for renewables to be considered in the future energy strategy of Libya. The LCEP will perform a first
assessment of the economic perspective of implementing RE.
The optimization of the LCEP can only be performed in a time and resource efficient manner when
agreement, not only on the optimization method but also on the inputs, has been achieved among the
parties involved. The methods, inputs and scenarios described in this report have been thoroughly
discussed with the WB, GECOL and REAOL. This report compiles all relevant information on the
LCEP optimization model structure, its inputs, the scenarios proposed to analyse sensitivities of the
LCEP and the results of the LCEP optimization.
Since the market offers many solar and wind technology combinations, the Consultant assessed tech-
nical alternatives in a two-step approach. In a first step, the Consultant performed a high level qualita-
tive analyses based on market and maturity of the technologies aiming to narrow down the many solar
and wind technologies to those most competitive for Private Sector Participation (PSP) during imple-
mentation of the LCEP. In a second step, the Consultant assessed local related aspects such as re-
source, load & supply profile and grid connection. The result of this second step will be in the form of a
set of the most suitable technology alternatives according to both their competitiveness in PSP acqui-
sition and their suitability for the Libyan conditions.
In order to have a clear picture of the RE potential in Libya the Consultant has used sites and technol-
ogy configurations which are only representative in order to be able to model different RE options un-
der different meteorological conditions.
Simultaneously with these processes, the Consultant analysed the role of the RE in Libya and prelimi-
nary concluded, together with the stakeholders, on the scenarios to be part of the optimization pro-
cess. Ultimately, both the reference case and the set of scenarios were thoroughly discussed and
agreed amongst the stakeholders. The set of scenarios shall represent important questions that could
be raised by decision makers.
An integral part of the Consultant’s analyses is the LCEP model that has been designed for the scope
of this particular assignment. The Consultant has dedicated a whole section to give an overview of its
formulation and its approach, as well as the inputs, assumptions and side constraints defined for the
optimization and the scenarios.
A number of different scenarios were simulated, varying divers input data and constrains. The results
of these different scenarios are herein presented alongside with the Consultant’s conclusions and rec-
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ommendations. Constrains were implemented to identify the most realistic scenario as the reference
case. Conclusions and recommendations are discussed with the stakeholders in order to define the fi-
nal LCEP mix which will be used for the Strategic Plan Renewable Energies for Libya (SPREL).
Finally the Consultant will recommend next steps to be taken by the stakeholders to maintain, update
and adjust the LCEP to the changing market and technology conditions of RE.
The Consultant’s analyses are partially based on the results of tasks performed by other consultants in
parallel under assignment of the World Bank. Wherever the Consultant here refers to Task A, the
Consultant is referring to results shared by other consultants working in parallel.
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2. Background
The Least Cost Expansion Plan (the LCEP) analysis is the first step towards the preparation of a Stra-
tegic Plan for Renewable Energies in Libya (the SPREL). This LCEP model specification contains the
main inputs, assumptions, scenarios and sensitivities used by the Consultant to optimize the electricity
generation mix for Libya until 2030 – and explore the role of Renewable Energies (RE) in the country –
as a part of Task D, Strategic Plan for Renewable Energy Development, mandated by the World Bank.
Based on the data provided by Task A Libya has in principle sufficient oil and gas conventional power
plants to match the current peak demand. However, the technical availability of this installed capacity
is considerable reduced for different reasons including issues with fuel transport, missing spare parts
and maintenance or damaged infrastructure. Although, further conventional capacity is currently under
development (see section 4.2), there are at least three important arguments for renewables to be con-
sidered:
First, there is the economic perspective. The efficiency of old conventional power plants is typi-
cally low and they use fuels that could otherwise be exported. This opens a window of opportunity
for RE as fuel saver as long as the costs of RE are lower than the (short-term) marginal cost of
conventional plants. As Libya possess very favourable renewable energy resources, a competitive
scenario is likely. This allows bringing further saving due to private sector participation (PSP) on
the generation site combined with PPA contracting to allow competitive pricing schemes.
Second, there is the issue of energy security and grid stability. As most conventional power plants
are located along the coast of Libya in particular remote locations in the centre and south (where
solar resource conditions are most favourable), RE could be used to balance the grid and to in-
crease energy security.
Third, there is the long-term perspective. Given the abundance of renewable energy resources,
the increasing opportunity costs of conventional power plants and the need for efficient electricity
pricing schemes, increasing the share of renewable in the power plant fleet is politically and eco-
nomically strongly recommended.
Typically, in order to determine the share of RE in any given grid goals in terms of the RE share, either
of the total energy produced or the total peak capacity installed, in percentage are set. The Consultant
will follow a different approach for this assignment following the economic rational of opportunity costs
and competitive pricing.
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3. Approach and Methodology
The steps below provide a brief high-level description of the overall methodology applied to determine
the least cost RE mix for Libya until 2030. The intention of this section is to present an overview of
previous analyses undertaken by the Consultant to define the set of inputs and assumptions within this
note. These analyses will be elaborated in detail in the Energy Mix and Renewable Resource As-
sessment Report part of this assignment.
Review of the role of RE in Libya: A descriptive review of the current status of RE in Libya and
the potential advantages of their implementation in a future generation mix;
High level qualitative analysis of the solar and wind alternatives: The result of this second step
are a set of the most suitable technology alternatives according to both their competitiveness in
PSP acquisition and their suitability for the Libyan conditions;
Appraisal of wind and solar resource: Review of the overall wind and solar resource based on
satellite data and cross check with existing ground data for a determination of the most suitable ar-
eas for implementation of solar and wind projects;
Appraisal of load and supply characteristics: The daily, weekly and seasonal load behaviour
was characterized alongside with projection for the conventional power supply in Libya (existing
and planned);
Grid connection alternatives: Review of existing transmission system expansion studies as well
as preliminary identification of potential connection points close to areas and sites suitable for wind
and solar power implementation;
Site restrictions and environmental aspects: A desktop review of potential site restrictions
based on existing freeware digital mapping in order to identify potential major obstacles and availa-
bility of suitable land for RE developments;
Technology configurations: Definition of configurations of solar and wind facilities which better
reflect the current and future market conditions and which are highly competitive within a PSP pro-
curement process. These configurations are only exemplary at this stage and not fixed for future
project developments or procurement processes;
Set of areas and configurations for the LCEP optimization: Definition of a reasonable set of
sites and technology configurations for preparation of performance indicators and incorporation in
the LCEP model. This set of areas and configurations is only exemplary and serves the goal of in-
corporating a representative picture of the performance of RE facilities in Libya; and
LCEP optimization: Set up the LCEP model together with the necessary assumptions, inputs, side
constraints, scenarios and sensitivities. Run the LCEP optimization, scenarios, sensitivities and
analysis of results.
The methods, inputs and scenarios applied have been thoroughly discussed with WB, GECOL and
REAOL in different sessions.
The Consultant’s analyses are partially based on the results of tasks performed by other consultants in
parallel under assignment of the World Bank. Wherever the Consultant here refers to either Task A or
Task B, the Consultant is referring to results shared by other consultants working in parallel.
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4. Load and Supply Characteristics
There are many aspects important for integrating RE into an existing network, however in order to
capture the order of magnitude and profiles of the demand that shall be satisfied by RE and for the
purposes of the LCEP, the following aspects relating to load and supply were considered:
Hourly seasonal daily, weekly and annual load in Libya;
Baseline of conventional power plants existing and planned; and
Capacity factors and supply profiles of RE at different representative locations as they depend
strongly on the location i.e. resources change substantially with changes thereof.
4.1 Load Characteristics and Demand Projections
Figure 4-1 shows the seasonal load behaviour for the year of 2016. Load peaks not only occur in
summer from 20 to 22 hours but also in winter (January) at 18 hours. An important fact is that these
peaks occur at times with no daylight in both seasons, thus initially not beneficiating solar technologies
without energy storage, but potentially offering a good match with wind power supply curves.
Figure 4-1: Exemplary daily profiles of monthly average load curves (MW)
Hourly load values for the complete year of 2016 were provided in electronic format by GECOL.
2000
2500
3000
3500
4000
4500
5000
5500
0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00
De
man
d in
MW
Time in h
January
February
July
September
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Demand growth projections have been prepared under Task A1. The demand growth has been pro-
jected by Task A consultants until 2030 across two scenarios – Scenario-A representing lower de-
mand growth in a case where political instability continues, and Scenario-B representing higher de-
mand growth in a case where political stability allows rapid development of mega-projects leading to
greater demand for electricity (see Figure 4-2).
The Consultants have based and harmonized assumptions of demand on the results of the Task-A
projections. Estimation of growth in hourly demand for the LCEP is based on the actual hourly load
values provided by GECOL for the year of 2016 adjusted to the yearly aggregate demand assessed in
Task A.
Figure 4-2: Scenarios for electricity consumption until 2030 (Task A)
4.2 Supply Projections – Baseline of Conventional Power
In order to optimize the LCEP it is necessary to feed the model with the current and projected compo-
sition and performance of the conventional power fleet. Task A has defined this composition and per-
formance in two different scenarios i.e. the worst and the best case as shown in Figure 4-3. While the
best case assumes a scenario of quick recuperation of performance of conventional power plants, the
worst case assumes a rather moderate one.
1 PWC, Simplified gas consumption estimate, World Bank, May 2017
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Figure 4-3: Scenarios of GECOL’s generation and T&D (Task A)
It is reasonable to assume that if RE can be deployed substantially in Libya from 2022 also the recu-
peration of availability and capacity of the conventional power would be feasible. The base case of the
LCEP assumes the best case of Task A. One additional scenario will deal with Task A’s worst case
(see section 7).
Table 4-1 and Table 4-2 set out the complete baselines of conventional power plants as integrated in
the LCEP.
Variable
Scenario
name
(2017-
2030)
Existing plantsUnder construction and
contracted plantsPlanned plants
Overhauls/
major
maintenance
• Each year: 4 units overdue from
past years + all overhauls of newly
due units
• Cleared by 2024Not applicable Not applicable
• Each year: 15 units overdue from
past years + all overhauls of newly
due units
• Cleared by 2020
Fuel
constraints
• Resolved by 2024
• None considered after
No constraints on fuel supply
considered
Not included
• Resolved by 2020
• None considered after
No constraints on fuel supply
considered
Derating
factor
• 0% for steam turbines
• 12% to 20% for single cycle and
combined cycle gas turbines
depending on historical derating and
location
• 0% for steam turbines
• 12% to 20% for single cycle and
combined cycle gas turbines
depending on geographical location
Not included
• 0% for steam turbines
• 12% to 20% for gas turbines
depending on geographic location
1
2
3
Best
Worst
Best
Worst
Best
Worst
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Table 4-1: Power plants for LCEP model – Worst case (Source: Task A)
Table 4-2: Power plants for LCEP model – Best case (Source: Task A)
WORST case
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Type of plant Power Station 10243 10832 10153 11555 13058 13615 13835 14185 14185 14101 13401 12801 12801 12801 12801
Existing Various Small / rented 543 513 100 100 100 100 100 100 100 100 100 100 100 100 100
Steam Khoms 480 480 480 480 480 480
Derna 130 130
Tobruk 130 130
Misurata Steel 504 504 84 84 84 84 84 84 84
Gulf 350 350 350 350 350 350 350 350 350 350 350 350 350 350 350
Tripoli West 370 370 240 240 240
Benghazi North 80 80
Gas Tripoli South 500 594 594 594 594 594 594 594 594 594 94 94 94 94 94
Zwetina 770 770 770 770 770 770 770 770 770 770 570 570 570 570 570
Khoms 1 600 600 600 600 600 600 600 600 600 600 600
Western Mountain 936 936 936 936 936 936 936 936 936 936 936 936 936 936 936
Sarir 855 855 855 855 855 855 855 855 855 855 855 855 855 855 855
Khoms 2 (Fast Track) 0 525 525 525 525 525 525 525 525 525 525 525 525 525 525
CC Zawia 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440
Benghazi North 1 915 915 915 915 915 915 915 915 915 915 915 915 915 915 915
Misurata 820 820 820 820 820 820 820 820 820 820 820 820 820 820 820
Benghazi North 2 820 820 820 820 820 820 820 820 820 820 820 820 820 820 820
Under contr. Steam Gulf 1050 1050 1050 1050 1050 1050 1050 1050 1050 1050 1050 1050
/ contracted Tripoli West 167 668 1018 1718 2068 2068 2068 2068 2068 2068 2068 2068
Tripoli East 127 254 254 254 254 254 254 254 254 254 254
Gas Ubari 624 624 624 624 624 624 624 624 624 624 624 624 624
Misurata 320 640 640 640 640 640 640 640 640 640 640
Tobruk 185 740 740 740 740 740 740 740 740 740 740 740
Proposed Steam Tripoli East
Tobruk 2
Derna 2
Benghazi West
Gas Sabha
Tripoli South 2
CC Misurata
Mellitah
Zweitina 2
Tobruk
Aboukammash
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Type of plant Power Station 10243 10832 10641 12043 13546 14103 15658 18263 19463 20903 21728 22378 24028 24578 23586
Existing Various Small / rented 543 513 160 160 160 160 160 160 160 100 100 100 100 100 100
Steam Khoms 480 480 480 480 480 480 480 480 480 480 480 480 480 480
Derna 130 130 130 130 130 130 130 130 130 130 130 130 130 130
Tobruk 130 130 130 130 130 130 130 130 130 130 130 130 130 130
Misurata Steel 504 504 252 252 252 252 252 252 252 252 252 252 252 252
Gulf 350 350 350 350 350 350 350 350 350 350 350 350 350 350 350
Tripoli West 370 370 240 240 240
Benghazi North 80 80
Gas Tripoli South 500 594 594 594 594 594 594 594 594 594 94 94 94 94 94
Zwetina 770 770 770 770 770 770 770 770 770 770 570 570 570 570 570
Khoms 1 600 600 600 600 600 600 600 600 600 600 600
Western Mountain 936 936 936 936 936 936 936 936 936 936 936 936 936 936 936
Sarir 855 855 855 855 855 855 855 855 855 855 855 855 855 855 855
Khoms 2 (Fast Track) 0 525 525 525 525 525 525 525 525 525 525 525 525 525 525
CC Zawia 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440 1440
Benghazi North 1 915 915 915 915 915 915 915 915 915 915 915 915 915 915 915
Misurata 820 820 820 820 820 820 820 820 820 820 820 820 820 820 820
Benghazi North 2 820 820 820 820 820 820 820 820 820 820 820 820 820 820 820
Under contr. Steam Gulf 1050 1050 1050 1050 1050 1050 1050 1050 1050 1050 1050 1050
/ contracted Tripoli West 167 668 1018 1718 2068 2068 2068 2068 2068 2068 2068 2068
Tripoli East 127 254 254 254 254 254 254 254 254 254 254
Gas Ubari 624 624 624 624 624 624 624 624 624 624 624 624 624
Misurata 320 640 640 640 640 640 640 640 640 640 640
Tobruk 185 740 740 740 740 740 740 740 740 740 740 740
Proposed Steam Tripoli East 700 1400 1400 1400 1400 1400 1400 1400
Tobruk 2 700 700 700 700 700 700
Derna 2 700 700 700 700 700 700 700 700
Benghazi West 700 1400 1400 1400 1400
Gas Sabha 855 855 855 855 855 855 855 855 855
Tripoli South 2 855 855 855 855 855 855 855 855
CC Misurata 500 750 750 750 750 750 750
Mellitah 550 1100 1650 1650 1650
Zweitina 2 550 825 825 825 825 825
Tobruk 550 825 825
Aboukammash 550 825 825
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5. Areas for the LCEP
For the purpose of obtaining a representative picture of the potential of RE in Libya the Consultant has
identified representative areas for installation of RE facilities as shown in Figure 5-1. This section pre-
sents an overview on how these areas were defined and the exemplary sites considered therein.
NOTE: Sites and technology configurations performed by the Consultant within this analysis are only
representative in order to model the RE potential in different regions in Libya and in no case substitute
proper site selection and feasibility studies. Technologies and sites part of an international tender pro-
cess shall be defined with specific studies in order to obtain the best value for money for each case.
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Figure 5-1: Preselected areas for the LCEP
In order to be able to estimate key performance indicators of representative solar and wind configura-
tions at potential areas in Libya the Consultant has:
a. Performed a high level qualitative analysis of the solar and wind alternatives in order to config-
ure a set of representative technology alternatives and technology configurations which will al-
low for simulation and estimation of key performance indicators, as well as cost indicators, to be
entered into the LCEP such as energy yield, supply profiles, efficiency, capacity factors, CAPEX
and OPEX (see Table 6-1);
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b. Appraised the Libyan wind and solar resource identifying within the areas selected the regions
with suitable wind and solar resource. This appraisal included the existing studies and available
ground measurement data;
c. Preliminarily reviewed grid connection alternatives based on existing transmission system ex-
pansion studies and potential connection points close to areas and sites suitable for wind and
solar power implementation. Distances to substations were roughly estimated in order to add
CAPEX for transmission connection (see section 6.2.4);
d. Assumed that water availability will not be considered a major issue since CSP plants will be
equipped with dry cooling systems;
e. Verified area availability for the different technology configuration. Whereas the area available
at some sites is suitable for PV, CSP and wind configurations other areas are only suitable for
one or two technologies. For the case of solar technologies larger areas were considered for
CSP due to the storage capability and hence the larger solar field. In general, areas considered
for the LCEP shall be large enough to reduce issues related to exclusion due to environmental
aspects (e.g. natural reserves) or land use (e.g. areas reserved for oil activities);
f. Verified site restrictions and environmental aspects by means of a desktop review of potential
site restrictions based on existing freeware digital mapping aiming to identify potential major ob-
stacles and availability of suitable land for RE developments; and
g. Prepared a set of representative sites2 and technology configurations (see Annex III, Table 3-1)
to be implemented in the LCEP model in the form of performance and cost data of solar and
wind options in Libya. This data was calculated by means of simulation of technology configura-
tions at the sites selected.
Table 5-1: Technology configuration for LCEP
RE Technology Alternative Technology Configuration
PV Crystalline / Thin film (CdTe) 50 and 100 MWac fix mounted and
1-axis tracked with p-Si modules
and central inverter;
One configuration crystalline fixed
mounted of 50 MWac and 3 hours
for the site in Sebah for comparison
purposes
Fixed mounted / One axis tracked
Central and string inverter configurations depend-
ing on the size
Li-Ion Long-duration Energy Storage (3 hours)
Wind Upwind / 3 blades rotors / horizontal axis 50 MW wind park; 2 MW turbines,
90 m hub height, 90 m diameter;
100 MW wind park; 3.5 MW tur-
bines; 110/120 m hub height; ap-
prox. 120 m diameter.
Onshore
Hub heights: 80 – 120 m
Rotor diameters: 90 – 136 m
Site classification II and III
Direct drive / gearbox
Double Feed Induction Generator (DFIG) / Fully
rated converter type (Type 3 and Type 4)
CSP Parabolic trough with thermal oil as HTF and mol-
ten salt TES
100 MWgross PT and Molten Salt
tower with TES of 7 to 10 FLH
(techno-economic optimization of
SM and TES capacity);
100 MWgross PT and molten salt
tower with TES of 13 to 15 FLH
(base load configuration)
Central Receiver Systems with molten salt as HTF
and TES
Air cooled condenser system
2 Sites defined within this assignment are only exemplary to appraise presentative performance data of RE in different areas of
Libya. This assignment does not intend to select sites for any type of investment or feasibility thereof.
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RE Technology Alternative Technology Configuration
Battery Li-Ion battery of Long-Duration energy Storage Li-Ion modules of 10 MW and 7
hours
In addition to this and following GECOL recommendation that a share of RE facilities may be installed
preferably more in the south of the overall transmission and distribution grid (e.g. in the southern cen-
tres of the two main North-south branches of the grid), representatives areas for the south i.e. Thala
and Jagboub were incorporated in the LCEP in agreement with GECOL and REAOL.
6. Conditions, Constrains and Inputs into LCEP
This section presents the description of the LCEP model and the inputs, assumptions and constraints
part of the optimization process. It is not the intention to describe herein the detail of the formulation
and the code used for the MATLAB tool as this will require a separate dedicated document which is
not the purpose of this assignment.
6.1 The LCEP Model
The Consultant’s LCEP model is an energy system model which allows the determination and the de-
velopment of electricity supply systems based on a least cost optimization approach. The model ap-
proach is applicable to various supply systems with different background conditions. Therefore the
model is able to consider renewables as well as conventional power plants. The determination of the
least cost electricity supply systems is significantly dependent on the available input parameter to the
model. Mainly the model needs information on:
Existing or planned installed capacities of supply systems;
Technical and economic characteristics of electricity generating configurations;
Hourly time series of renewable power generation (in spatial resolution); and
Electricity demand (in temporal resolution).
Figure 6-1: LCEP Model
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The Consultant’s LCEP model is programmed in a modular structure, in which each supply technolo-
gy/unit is represented by an independent module which is characterized by technical and economic
specifications. The optimization relies on a perfect foresight modelling approach.
The LCEP model is implemented in the software MATLAB, using a mixed-integer linear optimization
approach and has been developed for the conditions of the scope of this particular assignment. The
model has been tested for different cases within this assignment to check the validity of its results. A
full validation of the model can only be done by running the same data with a similar model and com-
paring the results. If necessary, such task is to be implemented by a third party under a separate as-
signment.
Due to the consideration of fluctuating behaviour renewable configurations, it is necessary to consider
a high temporal resolution for the analysis of operation of suppliers in the LCEP model. The optimiza-
tion of the Libyan generation system relies on an hourly basis of 8,760 hours per year. Although, the
model can cover that time span and resolution, depending on the complexity of the power system, the
expansion horizon is subdivided into optimization horizons of 6-8 years. Parts of the results are stored
for the final solution and some of them are used for the next optimization horizon.
6.1.1 The LCEP Target Function
The LCEP will be based on the minimization of CAPEX and OPEX of the solar and wind mix for Libya
by means of a target function that includes these parameters together with performance data of each
technology configuration such as capacity and energy production. In parallel, the target function mini-
mizes the costs of stock and planned conventional power plants, but the overall focus is still on the op-
timization of the solar and wind mix for Libya. The target function is defined as:
𝐹𝑚𝑖𝑛 = ∑ [𝑃𝑖𝑛𝑠𝑡,𝑝𝑝 𝑎 ∙ (𝐶𝐴𝑃𝐸𝑋𝑝𝑝,𝑎 + 𝑂𝑃𝐸𝑋𝑓𝑖𝑥,𝑝𝑝,𝑎) + ∑ 𝐸𝑝𝑝,𝑎,𝑡 ∙ (𝑂𝑃𝐸𝑋𝑣𝑎𝑟,𝑝𝑝,𝑎,𝑡)
8760
𝑡=1
]
2030
𝑎=2017
𝐶𝐴𝑃𝐸𝑋𝑝𝑝,𝑎 = (𝐼𝑛𝑣𝑒𝑠𝑡𝑡𝑜𝑡𝑎𝑙,𝑝𝑝 + 𝑇𝑟𝑎𝑛𝑠𝑚𝑖𝑠𝑠𝑖𝑜𝑛𝑝𝑝) ∗ 𝑎𝑛𝑝𝑝 ∙1
1 + 𝑑𝑖𝑠𝑐𝑝𝑝𝑎−2017
𝑂𝑃𝐸𝑋𝑣𝑎𝑟,𝑝𝑝,𝑎,𝑡 =1
𝜂𝑝𝑝,𝑎
∙ (𝐹𝑢𝑒𝑙𝐶𝑜𝑠𝑡𝑝𝑝,𝑎,𝑡 + 𝑂𝑀𝑣𝑎𝑟,𝑝𝑝,𝑎,𝑡+𝐶𝑂2𝑝𝑝,𝑎,𝑡) ∙1
1 + 𝑑𝑖𝑠𝑐𝑝𝑝𝑎−2017
Where:
Fmin : Total cost of RE mix to be minimized [USD]
Pinst,pp,a : Annual gross installed capacity reduced by the technical availability per plant
[MWgross-a]
Epp,a : Annual gross energy production per plant [MWhgross-a]
𝐸𝑝𝑝,𝑎,𝑡 = 𝐸𝑝𝑝,𝑎,𝑡 ∙ (1 − 𝐷𝑒𝑔𝑝𝑝,𝑎)
𝐶𝐴𝑃𝐸𝑋𝑝𝑝,𝑎 : Annual expenditures related to the power plant capacity [USD/MWgross]
Investtotal,pp : Capital expenditures including cost of financing per plant [USD/MWgross]
Transmissionpp,: Fixed expenditures for additional grid connection [USD/km] (see section 6.2.4)
OPEXfix,pp,a : Annual fixed operational expenditures per plant [USD/MWgross-a]
OPEXvar,pp,a,t : Aggregated variable operational expenditures per plant [USD/MWh-a]
FuelCostpp,a,t : Fuel costs per plant [USD/MWh-a]
OMvar,pp,a,t : Variable operation expenditures per plant [USD/MWh-a]
CO2pp,a,t : Cost for CO2 emissions per plant [USD/MWh-a]
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𝑝𝑝𝑙𝑖𝑓𝑒𝑡𝑖𝑚𝑒 : Depreciation time [a];
𝜂𝑝𝑝,𝑎 : The thermal efficiency describes the conversion of thermal energy into electrical
energy of the respective plant. [%/100] 𝐷𝑒𝑔𝑝𝑝,𝑎 : Annual degradation of the respective plant [%/100]
𝑑𝑖𝑠𝑐𝑎 : Discount rate [%/100]
𝑎𝑛𝑝𝑝 : Annuity factor [1
a] 𝑎𝑛 =
𝑖𝑝𝑝∙(1+𝑖𝑝𝑝)𝑝𝑝𝑙𝑖𝑓𝑒𝑡𝑖𝑚𝑒
(1+𝑖𝑝𝑝)𝑝𝑝𝑙𝑖𝑓𝑒𝑡𝑖𝑚𝑒−1
𝑖𝑝𝑝 : Interest rate [%/100]
6.1.2 Basis Years
In order to have a common basis for simulation of different technology configurations at different sites
the Consultant will prepare for a number of selected sites a Typical Meteorological Year (TMY) for
Global Horizontal Irradiation (GHI) and Direct Normal Irradiation (DNI), as well as wind speed and
wind direction. These basis years will allow for the estimation of the annual electricity production
(Epp,a) and levelised cost of electricity for each technology configuration at a defined site.
6.1.3 Solution Variables
6.1.3.1 Annual Gross Installed Capacity (Pinst,pp,a)
Is the gross installed capacity in MW of each conventional plant, as well as each solar and wind tech-
nology configuration (each plant) which will be installed per year e.g. the MW peak installed of a PV
plant. This capacity is reduced by the given technical availability.
6.1.3.2 Hourly Net Electricity Production (Epp,a,t)
The amount of energy produced gives the basis for estimating the revenues of selling electricity by the
plant. For the purpose of this study the annual electricity production serves as the basis for estimating
the variable operation expenses and indeed for estimation of the total electricity produced by the mix
of RE.
Epp,a,t is given in an hourly basis for the different sites (different basis years) and for each technology
configuration and describes which power plant/RE-configuration contribute to cover the demand in the
particular hour of the particular year of the expansion horizon. The maximum values for this solution
variable are based on the power plant capacity reduced by the thermal efficiency and on hourly supply
profiles for the renewable energy configurations. In the latter case the annual degradation of the tech-
nology output is considered (if necessary).
This energy is a net value after discounting the auxiliaries’ consumption the auxiliary consumption val-
ues will be given as a percentage of the gross electricity production for each plant.
6.1.3.3 Levelised Cost of Electricity (LCoE)
The standard method of estimation of electricity cost could be used, the Levelised Cost of Electrictiy
(LCoE).
If necessary, the LCoE could be estimated for each new plant separately and an average LCoE could
be calculated for each technology. The following (simplified) formula will be used:
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𝐿𝐶𝑜𝐸𝑝𝑝 =
∑𝐶𝐴𝑃𝐸𝑋𝑝𝑝,𝑎 + 𝑂𝑃𝐸𝑋𝑡𝑜𝑡𝑎𝑙,𝑝𝑝,𝑎
(1 + 𝑑𝑖𝑠𝑐𝑎)𝑎𝑛𝑎=0
∑𝐸𝑝𝑝,𝑎
(1 + 𝑑𝑖𝑠𝑐𝑎)𝑎𝑛𝑎=0
Where:
LCoEpp : Total LCoE per plant in USD/MWh;
CAPEXpp,a : Capital expenses in the year t for the corresponding plant in USD;
OPEXtotal,pp,a : Operation expenses in the year t in USD;
OPEXtotal = 𝑂𝑃𝐸𝑋𝑣𝑎𝑟 + 𝑂𝑃𝐸𝑋𝑓𝑖𝑥
Epp,a : Annual gross energy production per plant [MWhgross-a]
𝑑𝑖𝑠𝑐𝑎 : Discount rate [%/100]
𝑛 : Life time of the system [a]
6.1.4 Capacity Credit3
The capacity credit expresses the ‘firm’ capacity of renewable power supply technologies as a fraction
of total installed capacity of the particular power supply technology. As an example, wind turbines with
an installed capacity of 10 GW and a capacity credit of 20 % have a ‘firm’ capacity of 2 GW. This
means a reduction of 2 GW of other plants that has to cover the demand, compared to a situation with
no wind capacity. Due to the point that the capacity credit is a function of the installed capacity, the
relative capacity credit reduces with increasing penetration levels of the particular supply technology in
the system. This does not mean that less conventional capacity can be replaced, but rather that e.g. a
new wind plant added to a system with high wind power penetration levels will substitute less than the
first wind plants in the system.
The model is sensitive to capacity credit, for instance, in the case of Libya the capacity credit of PV-
systems is lower than the capacity credit of wind and CSP systems since there is no sun at the mo-
ment of peak load. Therefore, it is likely that the model finds a least cost optimization solution without
PV-systems. This effect is mainly caused because PV-systems are only partly able to provide ‘firm’
capacity during the hours of high demand.
The capacity credit is included in the model in the side constraint, which secures the covering of the
yearly peak load see section 6.3.2.
The capacity credit will be calculated in the following manner:
1. Calculation of the ‘firm’ capacity of stock power plants required to cover the demand. Convolu-
tion of probability distributions representing the technical availability of each stock power plant.
2. Calculation of the ‘firm’ capacity of stock power plants required to cover the demand + particular
RE-configuration. Convolution of probability distribution of ‘firm’ capacity of all stock power
plants with probability density function of RE-feed-in.
3. Difference between (1) and (2) represents the ‘firm’ capacity of the particular RE-configuration
The capacity credit is recalculated according to the stock power plants in different years of expansion
horizon.
To better assess the effects of the capacity credit for different technologies within the Libyan grid, the
Consultant will perform different optimizations in the form of scenarios for common discussion.
3 Planning for the renewable future: Long-term modelling and tools to expand variable renewable power in emerging econo-
mies. Abu Dhabi, 2017. – ISBN 978–92–95111–06–6
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6.1.5 Brief Notes on Modelling Approach
It is important to always consider that the focus of the LCEP model is to find the least cost mix of RE.
The following notes summarize general aspects of the modelling approach defined during the process:
In order to consider the effect of conventional power, the Consultant integrates standard conven-
tional power plants (i.e. a CCGT and a SCGT due to its peaker capabilities), which will be part of
the optimization process together with the RE. The standard conventional power plants perfor-
mances and cost indicators will follow suit to the assumptions made for plants under construction in
the baseline determined for the LCEP. These additional conventional power plants, if necessary by
the LCEP, will be available from 2021. Before this period, all possible occurring gaps in the electric-
ity supply are covered by modelled electricity imports. The Consultant considers that after 2021
electricity imports from Tunis or Egypt shall not be cheaper than local produced electricity in the
same conditions and thus no imports from 2021 are considered;
The model will perform an estimation of CO2 reduction and fuel savings in the results;
The modelling takes into consideration the existing and committed conventional power plants in the
base scenario;
Conversion of SCGTs to CCGTs are usually only recommended when the plants were designed for
a later conversion as they need further requirements such as cooling systems and further addition-
al land. This could be implemented if GECOL provides the set of data for such conversions;
The Consultant understands the need of competition between all feasible conventional technolo-
gies in a model. The technologies selected (i.e. SCGT and CCGT) with natural gas as fuel reflect
the most likely decision according to the conditions of Libya since, according to internal discussions
with the stakeholders, it is very unlikely that Libya will decide to install nuclear or coal power plants
within the horizon of this LCEP; and
Reserves are chiefly given by the existing pipeline of projects and the capacity credit of RE is inte-
grated in the model to consider if further reserves are required. In the model, a reserve capacity of
20% of the yearly peak load is considered to secure sufficient capacity in the system even if a sig-
nificant capacity is disconnected. A detailed analysis of reserves needed for balancing energy is
not considered at this preliminary stage of analysis.
6.2 Inputs to the model
6.2.1 Demand Growth
Refer to section 4.1 for details on the demand growth.
6.2.2 Existing and Pipeline Projects (Conventional)
Details on the existing line of pipeline projects are described in section 4.2.
6.2.3 RE Technology Configurations and Sites
Details on technology configurations are described within the related report "Least Cost Expansion
Plan Report; Technology Review" and sites are described in the annexes.
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6.2.4 RE Technology Costs and Values over Time
For each technology configuration the Consultant will estimate the fixed costs (CAPEX and OPEXfix)
and variable cost (OPEXvar) as total values in USD/MW inst and USD/MWh respectively to be entered
into the model.
CAPEX
Economies of scale, when necessary, will be considered within the direct CAPEX by reducing its spe-
cific cost according to the Consultant’s database. For instance in the case of a CSP plant the specific
cost of the different plant’s systems will be reduced proportional to the size of the plant.
CAPEX or capital expenses are costs that mainly occur during the project construction and are used
to buy fixed assets e.g. a power plant. Using the annuity method, the investment costs are distributed
over the lifetime of a power unit. Table 6-1 shows indicative CAPEX for the different configurations.
Special attention was given to the case of CSP CAPEX due to the substantial price reduction experi-
enced this year of 2017. The CSP CAPEX assumed by the Consultant as depicted in Table 6-1 in-
cludes the total investment cost including development, EPC and start-up costs. This price was as-
sumed to be similar to the level of the last auction in Dubai this year of 2017. Two further sensitivities
for more optimistic price reductions for CSP were analysed to evaluate their effect in the LCEP mix
composition.
An estimated cost of transmission line has been added in accordance to estimated distances to sub-
stations in the form of a single circuit overhead line of 230 kV estimated to 600,000 USD/km4.
OPEX
Operation expenses, OPEX, are ongoing costs for running the plant including staff salaries, admin-
istration, land lease (if applicable), insurances, service fees, cars and consumption of media such as
water among others.
Operation expenses are divided into fixed (OPEXfix,pp,a) and variable (OPEXvar,pp,a). For PV and wind
operation expenses are chiefly fixed expenses whereas for CSP the variable part of the operation ex-
penses is more relevant as they consume water and fossil fuels in function of the electricity produced
i.e. the capacity factor. While fixed operation expenses can be estimated as a function of the installed
capacity, variable operation expenses can be estimated as a function of the electricity produced.
Table 6-1 summarizes CAPEX and OPEX with the corresponding factors necessary for estimation of
total values for the different configurations to be used in the LCEP model.
Availability
Annual availability (avpp,a) is a function of the reliability and the maintainability of the plant and hence of
the quality of the equipment and the O&M strategy respectively. These values will be given as a per-
centage for each technology configuration representing the plant outage hours either planned or
forced varying from year to year to reflect major events such as overhauls. Energy production shall be
annually reduced in accordance with this percentage.
4 Capital Costs for Transmission and Substations, Updated recommendations for WECC Transmission Expansion Planning,
Prepared for Western Electricity Coordinating Council, Black & Veatch, February 2014
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Degradation
Equipment wears out over time affecting and reducing its efficiency. Efficiency shall be adjusted at a
certain percentage every year. Since this percentage is applied annually to the plant’s efficiency it is
important to apply this directly to the plant’s remaining efficiency and not as a percentage of the ener-
gy production.
For the purpose of this study, the degradation (Degpp,a) will be also given as an annual percentage for
each technology configuration bearing in mind that overhauls may partially recover the efficiency re-
ductions in major equipment such as steam turbines.
An annual degradation of 0.5% will be assumed for PV and CSP.
Potential of cost reduction
Each technology alternative selected has its own potential of cost reduction that depends on many
factors such as technological innovation, expansion of the industry, more competitors and volume of
production. For the purpose of this study, the Consultant will estimate a percentage of cost reduction
for each technology configuration in order to cover this effect over the period of analysis.
It is important to note that the factors affecting this figure cannot be foreseen with high degrees of cer-
tainty as they depend on many political and framework aspects which may change over time. The es-
timations made for this study are based on existing market researches however the Consultant will try
to keep its views as conservative as possible.
According to IRENA’s report the potential reduction of the costs of installed capacity of onshore wind
is about 12% from 2014 to 2025 (see technology assessment report). This potential of cost reduction
will be applied linearly to the LCEP5.
For the case of PV and CSP IRENA projections for cost reduction potential for 20256 could be around
65% and 37% for PV and CSP respectively. For the purposes of this analysis and considering the re-
cent substantial cost reductions for solar technologies between 2016 and 2017 the Consultant as-
sumes a potential of cost reduction of 20% until 2025 for both PV and CSP CAPEX in the LCEP and
linearly until 2030.
5 The Power to Change, Solar and Wind Cost Reduction Potential 2025, IRENA, June 2016
6 The Power to Change, Solar and Wind Cost Reduction Potential 2025, IRENA, June 2016
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Table 6-1: Main performance, cost and technical values for the RE technology configurations
Item Factors PV1
PV (fix)
50 MWAC
60 MWp
PV2
PV (fix)
100 MWAC
120 MWp
PV3
PV (1ax)
50 MWAC
60 MWp
PV4
PV (1ax)
100 MWAC
120 MWp
CSP1
CSP PTC1
100 MWgross
SM3/TES7
CSP2
CSP CRS1
100 MWgross
SM3/TES10
CSP3
CSP PTC2
100 MWgross
SM4/TES13
CSP4
CSP CRS2
100 MWgross
SM4/TES15
WIND1
Wind
50
MWgross
WIND2
Wind
100
MWgross
BTT1
Battery
standalone
10 MW
7 Hours
CAPEX Indirect &
direct
CAPEXtotal,pp,a (Total
Investment Costs)
M USD
/MWp,gross 1.0 0.97 1.1 1.07 4.46 5.07 6.05 6.53 1.67 1.63 3.27
CAPEXtotal,pp,a (Total
Investment Costs)
M USD 60.29 116.38 66.26 128.07 445.75 507.27 605.19 652.7 83.45 162.97 32.67
OPEXfix
O&M incl. staff sala-
ries, administrations,
land lease etc.
USD/
MWp/gross/
a
14 300 13 000 17 600 16 000 43 000 46 050 43 000 46 050 29 900 29 235 29 848
OPEXvar
Auxiliaries consump-
tion (e.g. fossil fuels)
USD /
MWh - - - - 3.50 2.70 3.50 2.70 - - -
OPEXtotal,pp,a T USD/a 858 1 560 1 056 1 920 5 592 5 868 6 047 6 329 1 495 2 923 298
Availability
Availability % 99 99 99 99 98 98 98 98 96 96 100
Degradation
Degradation %/a 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 - - 2
Potential of cost
reductionfor
CAPEX
Until 2025 % 20 20 20 20 20 20 20 20 12 12 30
From 2025 to 2030 % Linear Linear Linear Linear Linear Linear Linear Linear Linear linear 30
1 With medium to large thermal energy storage (7 to 10 FLH) as set out for PTC and CRS
2 With base load storage capacity similar to the last Dubai design
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6.2.5 Exogenous Assumptions – Fuel Price
For natural gas: Task B has provided the Consultant with the projection of LNG price (including mole-
cule, liquefaction and shipping) shown in Table 6-2. Task B also clarified that the price was projected
based on EIAs forecast and estimated as ~12% Brent (similar to Egypt and Pakistan contracts) and
that these values do not include the repayment of new infrastructure (i.e. regasification terminal / ex-
pansion or new pipelines).
Table 6-2: Projection of LNG prices until 2030 (Source : Task B)
Year 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
USD/MBtu 6.0 7.6 8.4 9.0 9.4 9.7 9.9 10.0 10.3 10.6 10.8 10.9 11.0 11.3
For Heavy Fuel Oil/Light Fuel Oil: As crude oil derivatives are highly correlated with the crude oil
prices it is assumed that crude oil growth rate projections could be applied for both product catego-
ries7. According to recent World Bank estimates crude oil prices are assumed to increase from 55
$/bbl (2017) to 80 $/bbl (2030) in nominal US dollars8. This would correspond to an annual (linear)
growth of 2.9 %.
Table 6-3: Summary of fuel cost projections for the LCEP9
Fuel Type Fuel Costs
[LD/m3]
Price develop-
ment
LHV
[MWh/m3]
LFO 550 +2.9 10,77
HFO 421 +2.9 10,99
Based on the data on conventional power plants as provided by Task A the Consultant estimated the
approximate share of fuel costs in the total OPEX of conventional power plants. For this share, the
Consultant applied the price increase projections for fuels and for the remaining non-fuel share the
dollar inflation rate.
6.2.6 Technology Configurations and Costs for New Conventional
The Consultant has made preliminary assumptions for estimation of CAPEX and OPEX for conven-
tional power in the Libyan system. These assumptions could be updated with the baseline of conven-
tional generation to be provided by TASK A and further information from GECOL if available.
Estimation of OPEX for non-RE will follow a similar structure as for RE by separating fixes and varia-
bles OPEX. While fixed OPEX can be based in historic data of GECOL power plants, variable OPEX
is, for conventional fossil-fired power plants, a sensitive aspect due to volatility of fuel prices.
For fixed and variable OPEX of non-RE, and their price development over the period of the LCEP, the
Consultant based his assumptions on a similar project carried out almost simultaneously for the World
7 Seeking Alpha (2015): https://seekingalpha.com/article/2918546-how-correlated-are-crude-oil-prices-to-finished-petroleum-
products 8 World Bank Commodities Price Forecast (2017): http://pubdocs.worldbank.org/en/926111485188873241/CMO-January-2017-
Forecasts.pdf 9 Other sources are: Price Development: Vuorinen, Asko; Planning of optimal power systems. s.L. Ekoenergo Oy, 2009
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Bank in Jordan10
. For the variable OPEX costs, the Consultant applies the prices described in section
6.2.5.
Values over time for conventional power are based on information provided by GECOL on efficiency
and availability of the plants. Different to RE, substantial technology breakthroughs of generation of
gas and steam power leading to considerable changes on availability and technology cost are not
foreseen in the horizon of the LCEP.
Degradation will be considered based on typical figures unless further information is provided by
GECOL. Information on major overhauls, if provided, can be included as such overhauls bring about
efficiency recoveries of the turbines.
Estimations for new non-RE plants were assumed according to Table 6-4. The Consultant could in-
corporate costs of major overhauls and repairs if information on the amount and time is provided. The
new conventional plants are added (if needed) to the supply portfolio in multiple of a 500 MW unit.
Table 6-4: CAPEX and OPEX estimations for new non-RE power plants (Source11
)
Technology
CAPEX
[$/MW]
(2017)12
Price de-
velopment
[%/a]
OPEX fix
[$/MW]
(2017)
Price de-
velopment
[%/a]
Technical
availability
[%]
Effi-
ciency
[%]
GT 800.000 0 5.690 0 88 37
CCGT 950.000 0 7.851 0 88 49
For the conventional plants, the base case will assume gas as preferred fuel from 2022. Meaning that
until 2021 the LCEP will use the current fuel mix (i.e. gas, HFO and LFO) as applicable according to
Task A and from 2022 the use of gas will be preferred. The model will usually decide for gas unless
the plant can only burn HFO or LFO.
6.3 Side constraints
Further to the assumptions so far described, the optimization process will need the implementation of
side constraints relevant to a more realistic utilization and implementation of both conventional and re-
newable energies. These side constraints are implemented as upper and lower bounds of the solution
variables, inequations and equations. Side constraints 6.3.1 and 6.3.2 form the backbone of the model
approach.
10
Possible roles of concentrating solar power in Jordan’s future electric power system; Draft Final Report, October 2, 2017; The
World Bank, Ernst & Young, Castalia and Fraunhofer ISE 11
Kehlhofer, Rolf, et al. Combined-Cycle Gas & Steam Turbine Power Plants. 3rd Edition. Tulsa : PennWell, 2009. pp. 24-26.
ISBN 978-1-59370-168-0. - International Renewable Energy Agency (IRENA). Renewable Energy Technologies: Cost Analysis - Concentrating Solar
Power. Bonn : IRENA, 2012. - National Renewable Energy Laboratory (NREL). Cost Report: Cost and Performance Data for Power Generation Techniques.
s.l. : Black & Veatch, 2012 12
Possible roles of concentrating solar power in Jordan’s future electric power system; Draft Final Report, October 2, 2017; The
World Bank, Ernst & Young, Castalia and Fraunhofer ISE
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6.3.1 Satisfaction of Demand
The demand in every time step during the different years of the expansion horizon has to be covered
by the available power of the different supply systems (or imports/exports). The number of time steps
within one year is dependent on the temporal resolution chosen for the optimization (here 8,760 h).
This constraint is mathematically implemented as an equation and is applied in all scenarios.
𝐸𝐷𝑒𝑚𝑎𝑛𝑑,𝑎,𝑡 = ∑ 𝐸𝑝𝑝,𝑎,𝑡
𝑚
𝑝𝑝=1
(+𝐸𝐼𝑛/𝑂𝑢𝑡)
𝐸𝐷𝑒𝑚𝑎𝑛𝑑,𝑎,𝑡: Electricity demand for every time step t and for every year a of the optimization horizon;
refer to section 4.1 for details on the demand profile and growth
𝑚: Number of power plants 𝐸𝐼𝑛/𝑂𝑢𝑡: Electricity exchanges of a region/country with a neighbouring region/country
6.3.2 Satisfaction of Peak Load Plus Reserve Capacity
To secure a high security of supply, the peak demand plus additional requested reserve capacities
need to be covered by the technical available capacities of the generation system. Due to the fluctuat-
ing supply-depend behaviour of renewable energies, their technical availability is integrated as capaci-
ty credit (refer to section 6.1.4). This constraint is mathematically implemented as an inequation and is
applied in all scenarios.
∑ −𝑃𝑎𝑣,𝑝𝑝,𝑎
𝑚
𝑝𝑝=1
≤ −(𝑃𝑝𝑒𝑎𝑘𝑙𝑜𝑑,𝑎 + 𝑃𝑟𝑒𝑠𝑣𝑒𝑟𝑣𝑒,𝑎)
𝑃𝑎𝑣,𝑝𝑝,𝑎 = 𝑃𝑖𝑛𝑠𝑡,𝑝𝑝,𝑎 ∙ 𝑎𝑣𝑝𝑝,𝑎
𝑎𝑣𝑝𝑝,𝑎: Availability of the power plant
𝑃𝑝𝑒𝑎𝑘𝑙𝑜𝑑,𝑎: Peak load in every year a of the optimization horizon
𝑃𝑟𝑒𝑠𝑣𝑒𝑟𝑣𝑒,𝑎: reserve capacity to secure a sufficient security of supply
6.3.3 Minimum Load Of Conventional Power Plants
A minimum load for the combined cycles and steam power plants of 23% will be set to reflect this
technical constraint in the optimization. This constraint is implemented through limiting the lower
bounds of the solution variable ‘hourly net electricity production’ and is applied in all scenarios.
6.3.4 Short Term and Long Term and Maximum RE Capacity
Capacity limits are integrated in the model since:
In the short-term a moderate growth of renewable energy capacity is expected as the country is
building its learning curve and establishing the necessary framework for RE implementation; and
In the long-term (until 2030 for the purpose of this assignment) an unlimited growth of renewable
energy capacity is deemed as not realistic.
RE will be implemented in two steps, i.e. short and long-term, as described below. While the short-
term considers capacity restrictions in order to give an indication of the sites13
which could be as-
sessed for the installation of the first RE projects in Libya during the first years, the long-term does not
consider constraints in capacity as the idea is to give an overall idea of the potential until 2030 for in-
13
Sites in the context of this study are to be considered exemplary and are only an indication of potential locations to be further
assessed and its feasibility determined.
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stallation of RE. It is necessary to perform updates of the LCEP beneficiating from the lessons learned
of the first RE projects
Short-term (from 2019 to 2021): Within this short–term, capacity constraints chiefly due to available
area will be roughly estimated in order to restrict the model to reasonable capacities within the are-
as. This constraint will only be applied to PV and wind configurations since only these configura-
tions are allowed by the model to be implemented within this short-term period as described in sec-
tion 6.3.5. The estimated restrictions are described in Table 6-5.
Long-term (from 2021): Additional to the wind and PV configurations this term will include CSP con-
figurations as they could be implemented within this timeframe. Rather than in specific locations,
this period considers areas for installation as depicted in the first column of Table 6-5. It is im-
portant to note that for the long-term, locations are to be determined in detail and further analyses
are necessary for their development and potential implementation. The applied long-term expan-
sion limits in MW of installed renewable capacity within the different years of the expansion horizon
is shown in Figure 6-2. The solver is allowed to deviate from these limits in a range of ~2.5%. This
value was chosen by the consultant to keep the RE capacity expansion in a realistic level.
Table 6-5: Short-term capacity restrictions for the LCEP areas in MW
Short-term capacity restrictions
[MW]
Area City/town Max.
Tripoli Aziziya 200
Tripoli Misallatha 400
Tripoli Misurata 200
Tripoli Assaba 200
Tripoli Zliten 200
Tripoli Jadu 200
Bengazhi Derna 100
Bengazhi Al Maqron 200
Bengazhi Al Tamimi 100
Bengazhi Shahat 50
Sebah Sebah 500
Sebah Edri 100
Ghadamis Ghadamis 50
Brega Brega 100
Hun Hun 100
Ghat Thala 200
Jagboub Jagboub 100
Jagboub Kufra1 100
Jagboub Kufra2 100
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Figure 6-2: Long-term expansion limits of RE capacity for the LCEP
Due to area restrictions for implementation of wind power in the areas selected sensitivities on the
wind capacity restriction have been incorporated (see section 8).
6.3.5 Year of Commissioning for New Conventional and Renewable Configu-rations
Since at least more than two years are needed for the development and implementation of a power
project, all renewable and conventional configurations that are not part of the stock portfolio or part of
the planned power plants will not be integrated in the supply profile before 2019.
In order to reflect the different levels of complexity of project development and construction durations
associated to each technology the following side constraints were implemented:
PV configurations could be in commercial operation from 2019; and
Wind/CCGT/GT/CSP configurations could be in commercial operation from 2021
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7. Scenarios
Scenarios are a main component of the LCEP analysis as they will allow the stakeholders to see
changes in the LCEP mix with changes in main inputs to the optimization. In order to define the LCEP
base case the Consultant will vary the share of RE, the combination of RE technologies and the utili-
zation factor of the conventional plants.
The LCEP base case will feature the final mix of configurations/sites, the capacity credit values and
the baseline of conventional power plants.
Table 7-1 summarizes the simulated and analysed scenarios.
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Table 7-1: Summary of scenarios
No
of
Mo
del R
un
Nam
e o
f S
cen
ari
o
Qu
esti
on
an
sw
ere
d
Exis
tin
g a
nd
co
ntr
acte
d p
ow
er
pla
nts
Dem
an
d g
row
th
Op
tio
n o
f R
E
Lim
ited
im
ple
men
tati
on
of
RE
(sh
ort
an
d lo
ng
-term
)
Win
d lim
itati
on
of
1 G
W
WA
CC
CS
P
Gas p
rice a
ssu
mp
tio
n
Sta
nd
alo
ne b
att
ery
pre-scenario status quo How does the power plant fleet oper-
ates without new conventional or new RE capacity?
Best case of Task A
Low demand growth (Case A of
task A) No - - -
Medium (gas=Opportunity cost)
No
Sc 4 No RE What is the least-cost expansion
without RE ? Best case of Task A
Low demand growth (Case A of
task A) No - - -
Medium (gas=Opportunity cost)
No
Sc 2 Base case What is the least cost expansion with no short and no long term constraint
on RE implementation?
Best case of Task A
Low demand growth (Case A of
task A) Yes
No shortterm and no long-
term No 4%
Medium (gas=Opportunity cost)
No
Sc 1 Constraints on RE
implementation
What is the least cost expansion with no long term constraint on RE im-
plementation?
Best case of Task A
Low demand growth (Case A of
task A) Yes
Yes (short term)
No 4% Medium
(gas=Opportunity cost) No
Sc 3a - WACC 4%
Constraints on RE implementation
What is the least cost expansion with short and long-term constraint on RE
implementation?
Best case of Task A
Low demand growth (Case A of
task A) Yes
Yes (short term and long term)
No 4% Medium
(gas=Opportunity cost) No
Sc 3a - WACC 6%
Constraints on RE implementation
What is the least cost expansion with short and long-term constraints on
RE implementation?
Best case of Task A
Low demand growth (Case A of
task A) Yes
Yes (short term and long term)
No 6% Medium
(gas=Opportunity cost) No
Sc 3b Constraints on RE
implementation
What is the least cost expansion with short and long-term constraints on
RE implementation and wind capaci-ty limitation?
Best case of Task A
Low demand growth (Case A of
task A) Yes
Yes (short term and long term)
Yes (1GW)
4% Medium
(gas=Opportunity cost) No
Sc 3c Constraints on RE
implementation
What is the least cost expansion with short and long-term constraints on
RE implementation and wind capaci-ty limitation?
Best case of Task A
Low demand growth (Case A of
task A) Yes
Yes (short term and long term)
Yes (1GW)
6% Medium
(gas=Opportunity cost) No
Sc 3d Constraints on RE
implementation
What is the least cost expansion with short and long-term constraints on
RE implementation and wind capaci-ty limitation?
Best case of Task A
Low demand growth (Case A of
task A) Yes
Yes (short term and long term)
Yes (1GW)
8% Medium
(gas=Opportunity cost) No
Sc 5
Slow recovery of suspended units,
availability, efficien-cy and technical
What would be the RE mix with slow recovery of suspended units, availa-bility, efficiency and technical loss-
es?
Worst case of Task A
Low demand growth (Case A of
task A) Yes
Yes (short term and long term)
Yes (1GW)
4% Medium
(gas=Opportunity cost) No
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No
of
Mo
del R
un
Nam
e o
f S
cen
ari
o
Qu
esti
on
an
sw
ere
d
Exis
tin
g a
nd
co
ntr
acte
d p
ow
er
pla
nts
Dem
an
d g
row
th
Op
tio
n o
f R
E
Lim
ited
im
ple
men
tati
on
of
RE
(sh
ort
an
d lo
ng
-term
)
Win
d lim
itati
on
of
1 G
W
WA
CC
CS
P
Gas p
rice a
ssu
mp
tio
n
Sta
nd
alo
ne b
att
ery
losses?
Sc 5
Slow recovery of suspended units,
availability, efficien-cy and technical
losses?
What would be the RE mix with slow recovery of suspended units, availa-bility, efficiency and technical loss-
es?
Worst case of Task A
Low demand growth (Case A of
task A) Yes
Yes (short term and long term)
Yes (1GW)
6% Medium
(gas=Opportunity cost) No
Sc 6 Cancellation of
committed conven-tional power plants
What would be the RE mix if the committed power plants were can-
celled?
Best case of Task A re-moving the committed
conventional power plants
Low demand growth (Case A of
task A) Yes
Yes (short term and long term)
Yes (1GW)
4% Medium
(gas=Opportunity cost) No
Sc 6 Cancellation of
committed conven-tional power plants
What would be the RE mix if the committed power plants were can-
celled?
Best case of Task A re-moving the committed
conventional power plants
Low demand growth (Case A of
task A) Yes
Yes (short term and long term)
Yes (1GW)
6% Medium
(gas=Opportunity cost) No
Sc 7 High demand
growth
What would be the RE mix if load in-creases faster due to High demand
growth?
Best case of Task A
High demand growth (Case B of
task A) Yes
Yes (short term and long term)
Yes (1GW)
4% Medium
(gas=Opportunity cost) No
Sc 7 High demand
growth
What would be the RE mix if load in-creases faster due to High demand
growth?
Best case of Task A
High demand growth (Case B of
task A) Yes
Yes (short term and long term)
Yes (1GW)
6% Medium
(gas=Opportunity cost) No
Sc 8 High fuel price What is the least cost expansion high
fuel prices? Best case of Task A
Low demand growth (Case A of
task A) Yes
Yes (short term and long term)
Yes (1GW)
4% High (gas=+20 %) No
Sc 8 High fuel price What is the least cost expansion high
fuel prices? Best case of Task A
Low demand growth (Case A of
task A) Yes
Yes (short term and long term)
Yes (1GW)
6% High (gas=+20 %) No
Sc 9 Low fuel price What is the least cost expansion low
fuel prices? Best case of Task A
Low demand growth (Case A of
task A) Yes
Yes (short term and long term)
Yes (1GW)
4% Low (gas=-20 %) No
Sc 9 Low fuel price What is the least cost expansion low
fuel prices? Best case of Task A
Low demand growth (Case A of
task A) Yes
Yes (short term and long term)
Yes (1GW)
6% Low (gas=-20 %) No
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8. Sensitivities
Further to the scenarios, the LCEP considers also sensitivities for the base case scenario.
Table 8-1: Summary of sensitivities
Sensitivity Assumptions
Effects of GHI attenuation of PV sites in the south on the electricity production*
Medium attenuation 5% reduction of elec-tricity production
High attenuation 10% reduction of elec-tricity production
CAPEX increase of PV sites in the south due to more com-plex transport and mobiliza-tion, as well as to cover sup-ply of reactive capacity. Ap-plied only once to the CAPEX *
Moderate CAPEX increase 4% increase in CAPEX
High CAPEX increase 8% increase in CAPEX
Consideration of optimistic CAPEX reduction of CSP
Optimistic CAPEX reduction Base case -10%
Very optimistic CAPEX re-duction
Base case -20%
Limit of total installed wind capacity in the LCEP
Strong Maximum 0.5 GW
Moderate Maximum 2 GW
Variations in Weighted Aver-age Capital Cost (WACC) for CSP**
Higher risk margin Base case +2%
Lower risk margin Base case -2%
* PV sites in the south consist of those sites located in the Sebah, Ghadamis, Brega, Hun,
Ghat and Jaboub. It is expected that sites in the south will be more affected by attenuation
of GHI due to sand and sand storms, subsequently reducing the expected energy produc-
tion. Also this sensitivity covers for CAPEX increase associated to remote locations and
additional equipment needed to provide reactive capacity
** WACC sensitivities are intended to reflect the effects of the evolution of the Libyan polit-
ical situation in terms of political instability and subsequently risk levels.
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9. Results of Scenario and Sensitivities
The analysis of the results let to a selection of scenarios demonstrating the main outcome of the exer-
cise. This chapter 9 will guide thru the development of the reference case finally defined as the most
realistic case to mirror the system and its expansion until 2030 from today's point of view.
Results of a system expansion following this scenario (reference case) are displayed and discussed.
Sensitivities and their impact in case of simulating these scenarios as well as the reasons for not de-
fining them as "reference case" are displayed.
9.1 Scenario 4 (Sc4), No RE
Generally, the first scenario analysed for this selection is the scenario which does not consider any re-
newables to be part of the energy supply system until 2030 (Sc4 in Table 7-1 and in Table 9-1). This
scenario reflects the situation that only new conventional CCGT plants will be installed, no renewables
will be implemented until 2030. Under this scenario, the additional conventional power to be installed
will be 3.5 GW, mainly commissioned in 2021. As the new power plants are somewhat more efficient
than the existing once, this scenario allows for a reduction of the specific costs over the whole optimi-
zation horizon of 1%, compared to the case that no additional installations will be executed.
An approach denying RE installations into the power generation system until 2030 would signify
that no considerable cost savings on fuel by cheaper renewables is realised in Libya. Also, Lib-
ya would be de-coupled by the global development towards a strong, competitive renewable
upscaling.
9.2 Scenario 2 (Sc2), Unlimited RE
A second scenario considered the implementation of RE power generators without restrictions (Sc 2 in
Table 7-1 and in Table 9-1). It reflects an unlimited growth of renewable energy projects. Consequent-
ly, no new conventional capacity is installed and 12.35 GW of renewable energy technologies will be
added until 2030. This scenario demonstrates the highest cost savings, summing up to a reduction of
the specific costs over the whole optimization horizon of 16%.
Figure 9-1 displays the time line of installations. No conventional power generators will be installed: As
early as possible (restricted installation for PV from 2019 and for wind from 2012 on, see chapter
6.3.5), PV as well as wind projects will be implemented, whereas PV can start from 2019 and wind
from 2021. Once wind projects can be implemented (due to the constrains only from 2012), only wind
projects will be implemented further on.
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Figure 9-1: Scenario 4, reflecting unlimited RE implementation of 12.35 GW until 2030
The model results in a high deployment of RE projects and could be appreciated from that point
of view. Anyhow, many constraints would need to be removed, e.g. of regulatory nature, capaci-
ty building, development, financing and implementation, etc. All these administrative and tech-
nical constrains would realistically require much more time and other efforts to be considered as
realistic. The amount of RE projects to be implemented until 2030 needs to be restricted to re-
flect a realistic scenario as a reference case.
9.3 Scenario 3c (Sc3c), Reference Case
The reference case is reflected in Sc3c (please refer to Table 7-1 and Table 9-1). This scenario re-
flects the "learnings" from the two scenarios mentioned above. The scenario 3c includes the needs for
renewables, but limits its implementation to 5 GW until 2030. This is the most realistic scenario, allow
for a saving in costs of about 6%. Here, the installation of renewable power generators is restricted
maximum 5 GW total RE installations into Libya's system until 2030. Additionally, 3 GW of new con-
ventional power plants (CCGT) will be installed.
Further on, the installation of wind power projects in Libya is limited to 1 GW until 2030. Reason is,
that it should be avoided to install too much wind power in one area of the country. This shall avoid
challenges in grid extension and, as a very important issue, the installation of wind power projects
which are all depending on same wind conditions as they would be projected to be installed in the
North where very good wind conditions prevail.
The reference case allows for a specific WACC for CSP at 6% (other RE technologies are at 8%).
CSP technology shall help to stabilize the system and as storage systems are combined, make power
generation from solar happen even at night. The reduced WACC reflects that CSP as a promising
technology might receive more (financial) support than the other renewable technologies.
The costs for the gas used in the conventional power plants follow a medium gas price scenario ap-
proach.
The result of the installation of new power plants is shown in Figure 9-2. Again, in 2019 only PV pro-
jects will be realized as this is the only technology being possible to install before 2021. In 2021 a
huge amount of CCGT plants and wind plants will be starting their operation. Due to the fact that a
specific WACC for CSP is considered, in 2027 the first CSP project will go alive.
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Figure 9-2: Newly installed capacity for the Reference Case
To identify the energy supply by different devices, Figure 9-3 shows the energy demand as a black
line ion top of the bars. The bars display the annual produced energy until 2030, from 2021 always ful-
filling the demand. The diagram differs between the different technologies. Looking into 2029 where
the share of renewables is the highest, it can be understood that the renewable share is less than
25%. So, a "challenging" impact onto the gird is not to be expected.
Figure 9-3: Reference case: Produced energy until 2030
For this case, the Consultant analysed the economic savings of this Sc3c in comparison to the men-
tioned Sc4 (scenario without RE). Figure 9-4 shows the results over the years. In this figure, the sav-
ings with regard to CAPEX and OPEX as well as to fuel costs are displayed. For the two different cat-
egories, both, the annual value and the NPV are shown. Considering the NPV bars, they are annually
beneath the 200 Mio USD level, but in case not considering the discount rate, values go up and for
fuel savings in 2030 more than 1,000 Mio USD are displayed!
Over the complete time line until 2030 fuel cost savings reach 6,421 / 1,615 Mio USD, CAPEX/ OPEX
savings are with 3,644 / 946 Mio USD (where in both cases the latter figure represents the NPV).
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Wrapping up the information from this comparison: Even with a realistic (and as such constrained sce-
nario) huge savings will be reached!
Figure 9-4: Cost comparison showing savings in Sc3c (reference) in compared to Sc4 (No RE)
The reference case reflects a realistic scenario for the development of RE power plants in the
Libyan grid system until 2030.
Albeit a number of restrictions, the case shows that even with a reasonable growth of RE in the
system a proper share of energy can be delivered into the grid at the end of the time interval,
being between 20 and 25% annually. This amount of renewable share will not challenge grid
systems.
A detailed analyses shows that there will be considerable amounts of saving in comparison to
the Sc4, No RE. E.g., fuel savings are summing up to more than 6,400 Mio USD, resulting in a
NPV of more than 1,600 Mio USD!
9.4 Sensitivities
There are constrains within the reference case for which sensitivities have been analysed. These fur-
ther analyses are summarized:
Sensitivity 1: The reference case considers a limitation of wind power to 1 GW. What happens in
case this constrain will be removed?
Sensitivity 2: The WACC for CSP is defined to be 6%. In case the WACC can be reduced to 4%,
how does the system look like, then?
Sensitivity 3: The gas price scenario where the reference case is based on is a moderate scenario.
What will be the impact on the LECP analysis in case the gas price will be either increased ot r
lowered?
Sensitivity 1
To understand the impact of the limitation of maximum 1 GW of wind power to be installed, a scenario
removing this limitation but keeping all other conditions of the reference case, has been executed
(Sc3a - WACC 6%, please refer to Table 7-1 and Table 9-1).
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The results of this scenario shows that the wind power would sum up to 4,1 GW., please see Figure
9-5. All these power plants would be installed in the coastal area and this means that a huge share of
the capacity is depending on the same resource and same meteorological conditions. This might
cause in-balances in the grid system. In general, with regard to the investment, wind power will not re-
place CCGTs but solar (both PV and CSP).
Figure 9-5: Sensitivity 1, no constrain for wind power
Analysing the energy delivered into the system in an annual resolution (Figure 9-6), it becomes quite
clear that solar technologies would be replaced by wind power. No significant higher share of renewa-
bles in the grid would be reached compared to the reference case. Anyhow, the specific costs will be
reduced by 1% compared to the reference case.
Figure 9-6: Sensitivity 1, no constrain for wind power, produced energy until 2030
With this sensitivity 1 the specific costs can be lowered by 1% additionally.
Having in mind
-The big disadvantage of having installed a very high share of the renewable technologies in
coastal areas and considering the resulting impact from wind conditions in the area;
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-The fact that currently most conventional generation systems are locaterd in the north of the
country;
-That installation of a proper share of RE generators in the south of the country;
-The high local grid penetration;
this scenario will not be considered to show a realistic case.
Sensitivity 2
Sensitivity 2 (Sc 3b in Table 7-1 and in Table 9-1) shall reflect the effect of lowering the WACC for
CSP projects to 4%. Generally, such a scenario makes sense to simulate as it can be useful to sup-
port promising technologies to come to the market and often development banks show specific pro-
grams for this including concessional loans.
Actually, the simulation based on a 4% WACC for CSP shows a huge impact on the capacity of CSP
plants to be installed under LCEP conditions. This scenario shows that 3,1 GW of CSP would be in-
stalled until 2030. The total amount of RE capacity will then be 4,8 GW. The installed power remains
same, and the reductions of specific cost are in the same range as for the reference scenario.
Figure 9-7: Sensitivity 2, WACC for CSP lowered to 4%,
With regard to the energy delivered, the graph (Figure 9-8) shows an increased amount of RE energy
in the system. In 2029, the share is about 6% higher than in the reference case.
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Figure 9-8: Sensitivity 2, WACC for CSP lowered to 4%, produced energy until 2030
Despite the positive effect to increase the RE share to almost 30% in 2029 and 2030, this case
shows the most important "adjusting screw" to increase the capacity of CSP projects. With a
WACC of 8% no CSP is considered by the solver, at 6% a reasonable share (0,4 GW until
2030) to support this technology is reached and with 4% the system focuses with (too) high
shares on CSP.
Consultant's view in this case is, that development banks are not going to soft loan so much
CSP technology (3,1 GW in this case) in one country. It might be useful to apply such scenario
only for a few plants (more than in the reference case) but this sensitivity 2 leads to results
which cannot be called "realistic".
Sensitivity 3
It is understandable that one says that the results are applicable only under the mentioned moderate
gas price scenario. So, this sensitivity 3 analyses the impact of changing gas price into both direction,
into increased price scenario and decreased price scenario. The "High Fuel Price scenario (Sc8 in Ta-
ble 7-1 and in Table 9-1) considers an increase of the price of 20% whereas the Low Fuel Price sce-
nario (Sc8 in Table 7-1 and in Table 9-1 foresees a decrease by 20%).
Both scenarios are displayed in one chart together with the reference case (please refer to Figure
9-9). Each scenario is reflected in one bar.
The different colors within the bars refer to different technologies. Depending on the scenario, the
conventional installations remain almost similar, only slight differences occur. Within the RE technolo-
gy mix, there is a big impact, and while PV installations remain almost similar, CSP and wind are
changing.
- 39 -
Libya SPREL – LCEP Final Report
LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx
Figure 9-9: Sensitivity 3, Fuel price variation
The most important outcome from this sensitivity is that the share of RE technology installations
is not sensitive against the fuel price! This means from economic point of view installing renew-
ables is in all three fuel price scenarios the right way forward.
On the other hand the sensitivity 3 shows that, depending on the fuel price development, it
makes sense to re-run such LCEP model whenever forecast for fuel prices changes.
9.5 Summary of Results
The results of the scenarios are summarized in Table 9-1 and a summary sensitivity analyses are dis-
played in Table 9-2.
Table 9-1 includes all described and analysed scenarios. Sc4 and Sc2 are highlighted yellow. These
scenarios are described in the beginning of this chapter 9, in 9.1 and 9.2. The reference case de-
scribed in chapter 9.3, is highlighted green, whereas the two sensitivity scenarios 1 and 2 are high-
lighted light green. The scenarios forming the basis for sensitivity 3 are highlighted grey.
- 40 -
Libya SPREL – LCEP Final Report
LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx
Table 9-1: Summary of scenario results
2020
2025
2030
Co
nven
tio
nal
Win
d
PV
CS
P
To
tal
RE
Imp
ort
ed
en
erg
y u
nti
l 2030 [
TW
h]
sto
ck C
CG
T
new
CC
GT
GT
ST
Gas s
avin
g [
Mio
m3 i
n 2
025/2
030]
CO
2 s
avin
g [
Mio
t C
O2 i
n
2025/2
030]
2025 0 0 0 0 0 2025 0,0 0,0
2030 0 0 0 0 0 2030 0,0 0,0
2025 3.500 0 0 0 0 2025 0,0 0,0
2030 3.500 0 0 0 0 2030 0,0 0,0
2025 0 5.850 4.700 0 10.550 2025 2,8 6,3
2030 0 7.650 4.700 0 12.350 2030 3,3 7,3
2025 0 5.850 4.700 0 10.550 2025 2,8 6,3
2030 0 7.700 4.700 0 12.400 2030 3,3 7,3
2025 2.000 7.200 2.650 100 9.950 2025 2,9 6,4
2030 2.000 8.500 3.750 300 12.550 2030 3,4 7,4
2025 3.000 2.050 750 200 3.000 2025 1,1 2,4
2030 3.000 4.000 750 200 4.950 2030 1,8 4,0
2025 3.000 2.250 750 0 3.000 2025 1,1 2,3
2030 3.000 4.100 750 0 4.850 2030 1,8 3,9
2025 3.000 600 750 1.600 2.950 2025 1,3 2,8
2030 3.000 850 850 3.100 4.800 2030 2,1 4,6
2025 3.000 600 2.350 0 2.950 2025 0,8 1,8
2030 3.000 850 3.350 400 4.600 2030 1,4 3,1
2025 2.500 550 2.350 0 2.900 2025 0,8 1,8
2030 2.500 800 3.700 0 4.500 2030 1,3 2,8
2025 3.500 600 800 1.600 3.000 2025 1,3 2,8
2030 4.500 950 800 3.100 4.850 2030 2,2 4,9
2025 4.000 600 2.350 0 2.950 2025 0,8 1,8
2030 4.000 950 2.500 1.600 5.050 2030 1,9 4,1
2025 2.500 450 800 1.600 2.850 2025 1,2 2,7
2030 3.000 1.000 800 3.100 4.900 2030 2,2 4,9
2025 3.000 600 1.950 0 2.550 2025 0,7 1,6
2030 3.500 900 2.300 1.800 5.000 2030 1,9 4,2
2025 3.500 500 800 1.600 2.900 2025 1,2 2,7
2030 3.500 850 850 3.000 4.700 2030 2,1 4,7
2025 3.500 500 2.150 0 2.650 2025 0,8 1,7
2030 4.000 900 3.100 700 4.700 2030 1,6 3,4
2025 3.000 600 700 1.700 3.000 2025 1,3 2,9
2030 3.000 850 700 3.400 4.950 2030 2,2 4,9
2025 3.500 600 2.000 300 2.900 2025 0,9 2,0
2030 3.500 950 2.100 2.000 5.050 2030 2,0 4,3
2025 2.500 600 2.350 0 2.950 2025 0,8 1,8
2030 2.500 900 2.900 900 4.700 2030 1,6 3,4
2025 2.500 600 2.350 0 2.950 2025 0,8 1,8
2030 2.500 900 3.800 0 4.700 2030 1,3 2,8
No
of
Mo
del
Ru
n
Nam
e o
f S
cen
ari
o
Qu
esti
on
an
sw
ere
d
Exis
tin
g a
nd
co
ntr
acte
d p
ow
er
pla
nts
Dem
an
d g
row
th
Op
tio
n o
f R
E
Lim
ited
im
ple
men
tati
on
of
RE
(sh
ort
an
d
lon
g-t
erm
)
Win
d l
imit
ati
on
of
1 G
W
WA
CC
CS
P
Gas p
rice a
ssu
mp
tio
n
Sta
nd
alo
ne b
att
ery
To
tal
CA
PE
X f
or
all
new
co
nfi
gu
rati
on
s o
ver
the w
ho
le l
ife t
ime
[mio
US
D (
NP
V)]
To
tal
OP
EX
Fix
un
til
2030
[mio
US
D (
NP
V)]
Fu
el
co
sts
un
til
2030
[mio
US
D (
NP
V)]
Devia
tio
n i
n s
pecif
ic c
osts
((s
um
of
CA
PE
X,
OP
EX
Fix
& O
PE
X V
ar
(NP
V))
/ p
rod
uced
ele
ctr
icty
[U
SD
/MW
h])
over
the w
ho
le
op
tim
izati
on
ho
rizo
n c
om
pare
d t
o t
he 'sta
tus
qu
o o
r 'r
efe
ren
ce s
cen
ari
o' [%
]
pre-scenario status quo
How does the power plant fleet operates
without new conventional or new RE
capacity?
Best case
of Task A
Low demand growth
(Case A of task A)No
52 68% 63% 4% 20%-16% 5% 15% 20%Low (gas=-20 %) No 2.100 1.500 12.100Sc 9 Low fuel priceWhat is the least cost expansion low
fuel prices?
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
Yes
(1GW)6%
52 67% 61% 4% 20%-16% 5% 15% 24%Low (gas=-20 %) No 2.700 1.500 12.000Sc 9 Low fuel priceWhat is the least cost expansion low
fuel prices?
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
Yes
(1GW)4%
53 68% 53% 3% 21%16% 5% 17% 31%0,06 High (gas=+20 %) No 4.100 1.500 17.300Sc 8 High fuel priceWhat is the least cost expansion high
fuel prices?
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
Yes
(1GW)
53 64% 51% 3% 21%15% 5% 24% 35%4% High (gas=+20 %) No 4.200 1.600 16.700Sc 8 High fuel priceWhat is the least cost expansion high
fuel prices?
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
Yes
(1GW)
17% 56 78% 81% 5%17.100 -7% 5% 11%Yes
(1GW)6%
Medium
(gas=Opportunity cost)No 3.100 1.500
20%
Sc 7 High demand growth
What would be the RE mix if load
increases faster due to High demand
growth?
Best case
of Task A
High demand
growth (Case B of
task A)
YesYes (short term
and long term)
24% 56 76% 77% 4%16.300 -7% 5% 18%Yes
(1GW)4%
Medium
(gas=Opportunity cost)No 4.100 1.600
20%
Sc 7 High demand growth
What would be the RE mix if load
increases faster due to High demand
growth?
Best case
of Task A
High demand
growth (Case B of
task A)
YesYes (short term
and long term)
13% 30% 57 49% 94%1.300 14.400 -3% 5%Yes (short term
and long term)
Yes
(1GW)6%
Medium
(gas=Opportunity cost)No 3.900Sc 6
Cancellation of
committed
conventional power
plants
What would be the RE mix if the
committed power plants were
cancelled?
Best case of
Task A
removing the
committed
Low demand growth
(Case A of task A)Yes
23% 36% 57 49% 90%1.400 13.800 -2% 5%Yes (short term
and long term)
Yes
(1GW)4%
Medium
(gas=Opportunity cost)No 4.100
6% 20%
93% 1% 20%
Sc 6
Cancellation of
committed
conventional power
plants
What would be the RE mix if the
committed power plants were
cancelled?
Best case of
Task A
removing the
committed
Low demand growth
(Case A of task A)Yes
9% 16% 30% 109 44%3.900 1.300 12.700 0%YesYes (short term
and long term)
Yes
(1GW)6%
Medium
(gas=Opportunity cost)No
6% 20%
Worst case
of Task A
Low demand growth
(Case A of task A)
8% 24% 35% 102 42%4.500 1.400 12.200 0%YesYes (short term
and long term)
Yes
(1GW)4%
Medium
(gas=Opportunity cost)No
Scenarios
Sc 5
Slow recovery of
suspended units,
availability, efficiency
and technical losses?
What would be the RE mix with slow
recovery of suspended units,
availability, efficiency and technical
losses?
Worst case
of Task A
Low demand growth
(Case A of task A)
15% 20% 55 69% 63%1.500 14.900 -6% 5%Yes (short term
and long term)
Yes
(1GW)8%
Medium
(gas=Opportunity cost)No 2.000
88% 1% 20%
Sc 5
Slow recovery of
suspended units,
availability, efficiency
and technical losses?
What would be the RE mix with slow
recovery of suspended units,
availability, efficiency and technical
losses?
3% 20%
Sc 3dConstraints on RE
implementation
What is the least cost expansion with
short and long-term constraints on RE
implementation and wind capacity
limitation?
Best case
of Task A
Low demand growth
(Case A of task A)Yes
15% 22% 55 68% 59%1.500 14.800 -6% 5%Yes (short term
and long term)
Yes
(1GW)6%
Medium
(gas=Opportunity cost)No 2.500
4% 20%
Sc 3cConstraints on RE
implementation
What is the least cost expansion with
short and long-term constraints on RE
implementation and wind capacity
limitation?
Best case
of Task A
Low demand growth
(Case A of task A)Yes
23% 33% 55 62% 51%1.600 14.000 -6% 5%Yes (short term
and long term)
Yes
(1GW)4%
Medium
(gas=Opportunity cost)No 4.000Sc 3b
Constraints on RE
implementation
What is the least cost expansion with
short and long-term constraints on RE
implementation and wind capacity
limitation?
Best case
of Task A
Low demand growth
(Case A of task A)Yes
20% 27% 55 65% 55%1.500 14.400 -7% 5%Yes (short term
and long term)No 6%
Medium
(gas=Opportunity cost)No 2.600
3% 20%
Sc 3a - WACC
6%
Constraints on RE
implementation
What is the least cost expansion with
short and long-term constraints on RE
implementation?
Best case
of Task A
Low demand growth
(Case A of task A)Yes
20% 28% 55 64% 54%1.500 14.300 -7% 5%Yes (short term
and long term)No 4%
Medium
(gas=Opportunity cost)No 2.700
Sc 3a - WACC
4%
Constraints on RE
implementation
What is the least cost expansion with
short and long-term constraint on RE
implementation?
Best case
of Task A
3% 20%
Low demand growth
(Case A of task A)Yes
49 41% 28% 3% 20%-12% 11% 53% 52%Medium
(gas=Opportunity cost)No 5.200 1.900 11.400
3% 20%
Sc 1Constraints on RE
implementation
What is the least cost expansion with
no long term constraint on RE
implementation?
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short
term)No 4%
45 42% 3% 20%-16% 28% 53% 52%6%Medium
(gas=Opportunity cost)No 6.200 2.000 10.200Sc 2 Base case
What is the least cost expansion with
no short and no long term constraint on
RE implementation?
Best case
of Task A
Low demand growth
(Case A of task A)Yes
No shortterm
and no
longterm
No
52% 45 42% 3%10.200 -16% 28% 53%No 4%Medium
(gas=Opportunity cost)No 6.200 2.000
20%
Definition of a reference case
Sc 2 Base case
What is the least cost expansion with
no short and no long term constraint on
RE implementation?
Best case
of Task A
Low demand growth
(Case A of task A)Yes
No shortterm
and no
longterm
0% 55 76% 73% 4%16.400 -1% 0% 0%- -Medium
(gas=Opportunity cost)No 800 1.400
20%
RE electricity share
(energy based [MWh])
[%]
Addition to installed capacity [MW]
(2030 includes the capacity installed
until 2025) average utilization rates [%]
14% 20%
Sc 4 No REWhat is the least-cost expansion
without RE ?
Best case
of Task A
Low demand growth
(Case A of task A)No -
0% 0% 63 80%1.300 17.000 0%- - -Medium
(gas=Opportunity cost)No 0
- 41 -
Libya SPREL – LCEP Final Report
LBY2560_TaskD_ StageI_LCEP_Updated FinalReport.docx
Table 9-2: Summary of sensitivity results
2020
2025
2030
Co
nven
tio
nal
Win
d
PV
CS
P
To
tal
RE
Imp
ort
ed
en
erg
y u
nti
l 2030 [
TW
h]
sto
ck C
CG
T
new
CC
GT
GT
ST
Gas s
avin
g [
Mio
m3 i
n 2
025/2
030]
CO
2 s
avin
g [
Mio
t C
O2 i
n
2025/2
030]
2025 3.000 600 800 1.600 3.000 2025 1,3 2,8
2030 3.000 1.000 950 3.000 4.950 2030 2,1 4,7
2025 3.000 400 2.350 0 2.750 2025 0,7 1,6
2030 3.000 900 3.400 400 4.700 2030 1,4 3,1
2025 3.000 600 900 1.200 2.700 2025 1,1 2,4
2030 3.000 950 1.000 3.000 4.950 2030 2,1 4,7
2025 3.000 600 2.300 0 2.900 2025 0,8 1,8
2030 3.000 1.000 3.350 400 4.750 2030 1,4 3,1
2025 3.000 600 800 1.600 3.000 2025 1,3 2,8
2030 3.000 750 850 3.100 4.700 2030 2,1 4,6
2025 3.000 500 2.350 0 2.850 2025 0,8 1,7
2030 3.000 1.000 3.400 700 5.100 2030 1,6 3,5
2025 3.000 600 900 1.500 3.000 2025 1,3 2,8
2030 3.000 950 950 2.900 4.800 2030 2,1 4,6
2025 3.000 600 2.350 400 3.350 2025 0,8 1,8
2030 3.000 900 3.400 400 4.700 2030 1,4 3,1
2025 3.000 500 700 1.700 2.900 2025 1,3 2,8
2030 3.000 950 800 3.300 5.050 2030 2,2 4,9
2025 3.000 550 2.000 400 2.950 2025 0,9 2,1
2030 3.000 950 2.200 1.600 4.750 2030 1,8 3,9
2025 2.500 600 700 1.700 3.000 2025 1,3 2,9
2030 2.500 800 700 3.200 4.700 2030 2,1 4,7
2025 3.000 600 800 1.600 3.000 2025 1,3 2,8
2030 3.000 1.000 850 3.000 4.850 2030 2,1 4,7
2025 3.000 300 900 1.800 3.000 2025 1,3 2,9
2030 3.000 500 950 3.500 4.950 2030 2,2 4,8
2025 2.500 300 2.650 0 2.950 2025 0,8 1,7
2030 2.500 500 4.000 200 4.700 2030 1,3 2,9
2025 3.000 950 750 1.000 2.700 2025 1,1 2,4
2030 3.000 1.850 800 2.100 4.750 2030 2,0 4,4
2025 3.000 1.250 1.750 0 3.000 2025 0,9 2,0
2030 3.000 1.850 2.850 500 5.200 2030 1,7 3,7
No
of
Mo
del
Ru
n
Nam
e o
f S
cen
ari
o
Qu
esti
on
an
sw
ere
d
Exis
tin
g a
nd
co
ntr
acte
d p
ow
er
pla
nts
Dem
an
d g
row
th
Op
tio
n o
f R
E
Lim
ited
im
ple
men
tati
on
of
RE
(sh
ort
an
d
lon
g-t
erm
)
Win
d l
imit
ati
on
of
1 G
W
WA
CC
CS
P
Gas p
rice a
ssu
mp
tio
n
Sta
nd
alo
ne b
att
ery
To
tal
CA
PE
X f
or
all
new
co
nfi
gu
rati
on
s o
ver
the w
ho
le l
ife t
ime
[mio
US
D (
NP
V)]
To
tal
OP
EX
Fix
un
til
2030
[mio
US
D (
NP
V)]
Fu
el
co
sts
un
til
2030
[mio
US
D (
NP
V)]
Devia
tio
n i
n s
pecif
ic c
osts
((s
um
of
CA
PE
X,
OP
EX
Fix
& O
PE
X V
ar
(NP
V))
/ p
rod
uced
ele
ctr
icty
[U
SD
/MW
h])
over
the w
ho
le
op
tim
izati
on
ho
rizo
n c
om
pare
d t
o t
he 'sta
tus
qu
o o
r 'r
efe
ren
ce s
cen
ari
o' [%
]
27% 55 67% 58% 3%14.600 0% 5% 17%Yes
(0,5GW)6%
Medium
(gas=Opportunity cost)No 2.900 1.500Wind 2 GW
Limit of total installed
wind capacity in the
LCEP - moderate
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
31% 55 64% 53% 3%14.200 0% 5% 20%Yes
(0,5GW)4%
Medium
(gas=Opportunity cost)No 3.500 1.600
20%
20%Wind 2 GW
Limit of total installed
wind capacity in the
LCEP - moderate
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
20% 55 69% 64% 4%14.900 0% 5% 15%Yes
(0,5GW)6%
Medium
(gas=Opportunity cost)No 2.200 1.500Wind 0,5 GW
Limit of total installed
wind capacity in the
LCEP - strong
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
34% 55 61% 51% 3%14.000 0% 5% 24%Yes
(0,5GW)4%
Medium
(gas=Opportunity cost)No 4.200 1.600
20%
20%Wind 0,5 GW
Limit of total installed
wind capacity in the
LCEP - strong
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
33% 55 62% 52% 3%14.000 0% 5% 24%Yes
(1GW)6%
Medium
(gas=Opportunity cost)No 4.000 1.600
20%
CSP - Very
optimistic
CAPEX
reduction
Consideration of
optimistic CAPEX
reduction of CSP
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
33% 55 62% 54% 3%14.000 -1% 5% 24%Yes
(1GW)4%
Medium
(gas=Opportunity cost)No 3.400 1.600
20%
CSP - Very
optimistic
CAPEX
reduction
Consideration of
optimistic CAPEX
reduction of CSP
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
28% 55 65% 56% 3%14.600 0% 5% 17%Yes
(1GW)6%
Medium
(gas=Opportunity cost)No 3.400 1.500
20%
CSP - Optimistic
CAPEX
reduction
Consideration of
optimistic CAPEX
reduction of CSP
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
35% 55 61% 51% 3%14.000 -1% 5% 23%Yes
(1GW)4%
Medium
(gas=Opportunity cost)No 3.800 1.600
20%
CSP - Optimistic
CAPEX
reduction
Consideration of
optimistic CAPEX
reduction of CSP
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
22% 55 68% 60% 3%14.800 0% 5% 15%Yes
(1GW)6%
Medium
(gas=Opportunity cost)No 2.600 1.500
20%
CAPEX South
+8%
CAPEX increase of
PV sites in the south
due to more complex
transport and
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
33% 55 63% 52% 3%14.100 0% 5% 23%Yes
(1GW)4%
Medium
(gas=Opportunity cost)No 3.900 1.600
20%
CAPEX South
+8%
CAPEX increase of
PV sites in the south
due to more complex
transport and
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
25% 55 68% 59% 3%14.800 0% 5% 14%Yes
(1GW)6%
Medium
(gas=Opportunity cost)No 2.900 1.500
20%
CAPEX South
+4%
CAPEX increase of
PV sites in the south
due to more complex
transport and
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
32% 55 62% 51% 3%14.000 0% 5% 24%Yes
(1GW)4%
Medium
(gas=Opportunity cost)No 3.900 1.600
20%
CAPEX South
+4%
CAPEX increase of
PV sites in the south
due to more complex
transport and
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
15% 22% 55 68% 60%1.500 14.800 0% 5%Yes (short term
and long term)
Yes
(1GW)6%
Medium
(gas=Opportunity cost)No 2.600GHI South -10%
Effects of GHI
attenuation of
PV sites in the south
on the
Best case
of Task A
Low demand growth
(Case A of task A)Yes
20% 33% 55 62% 53%1.600 14.100 0% 5%Yes (short term
and long term)
Yes
(1GW)4%
Medium
(gas=Opportunity cost)No 4.000GHI South -10%
Effects of GHI
attenuation of
PV sites in the south
on the
Best case
of Task A
3% 20%
Low demand growth
(Case A of task A)Yes
55 68% 60% 3% 20%0% 5% 14% 22%Medium
(gas=Opportunity cost)No 2.600 1.500 14.800
3% 20%
GHI South -5%
Effects of GHI
attenuation of
PV sites in the south
on the
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
Yes
(1GW)6%
55 62% 51% 3% 20%0% 5% 24% 33%Medium
(gas=Opportunity cost)No 4.000 1.600 14.000
Sensitivities
GHI South -5%
Effects of GHI
attenuation of
PV sites in the south
on the
Best case
of Task A
Low demand growth
(Case A of task A)Yes
Yes (short term
and long term)
Yes
(1GW)4%
RE electricity share
(energy based [MWh])
[%]
Addition to installed capacity [MW]
(2030 includes the capacity installed
until 2025) average utilization rates [%]
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10. LCEP Follow-up
The Consultant recommends the following actions for a successful implementation of the LCEP:
The LCEP is a dynamic tool, which needs to be constantly updated according to changes of the lo-
cal electricity system, electricity market, technology development and technology breakthroughs;
Constrains used to identify a realistic set-up and to identify the reference case need to be scruti-
nized permanently to up-date or adapt them whenever the situation occurs.
Also, whenever new results for more detailed meteorological resource analysis or more detailed
basic information for site selection are available, a re-run of the LCEP might bring new results.
After preparation of the Strategic Plan for Renewable Energy of Libya (the SPRE) based on out-
comes of the LCEP, an investment plan shall be refined and agreed upon;
Implementation of geospatial intelligence for the LCEP, which shall be used for coordination and
monitoring the implementation of the LCEP. Such system shall allow stakeholders to access vital
information of the LCEP, its infrastructure and each RE facility in real time;
Implementation of state-of-the-art measurement campaigns for the preferred wind and solar sites
identified in the LCEP;
Preparation of a master plan for implementation of the required infrastructure necessary for the
LCEP alongside with an investment plan;
Preparation of at least basic power system studies to verify the suitability of connection points and
transmission lines for the LCEP;
Preparation of an administrative structure at REAOL in charge of administration of the LCEP in-
cluding project management, as well as asset & facility management;
Prepare policies and guidelines in order to streamline the participation of the private sector with re-
gard to permitting, land securing and grid connection (this will be also addressed as part of the
SPREL included in this assignment); and
Preparation of a strategy for allocation of land to be centralized in the geospatial intelligence.
Libya - Supporting Electricity Sector Reform (P154606)
Contract No. 7181909 - Task D: Strategic Plan for Renewable Energy Development
Least Cost Expansion Plan Report Annex I – Solar and Wind Resource 12 December 2017
Client:
The World Bank
1818 H Street, N.W.
Washington, DC 20433
Consultant:
GOPA-International Energy Consultants GmbH
Justus-von-Liebig-Str. 1, 61352 Bad Homburg, Germany
Phone: +49-6172-1791-800; Fax: +49-6172-944 95 20
eMail: info@gopa-intec.de; www.gopa-intec.de
Suntrace GmbH
Grosse Elbstrasse 145c, 22767 Hamburg, Germany
Phone: +49-40-767 96 38 0; Fax: +49-40-767 96 38 20
www.suntrace.de
Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource
LBY2560_TaskD_ StageI_LCEP_Report_AnnexI_Resource.docx
Table of Contents Page
1. Solar and Wind Resource 1
1.1 Solar Resource 1
1.1.1 Global Horizontal Irradiance (GHI) - PV 2
1.1.2 Direct Normal Irradiance (DNI) - CSP 2
1.2 Wind Resource 5
1.2.1 Wind Resource – Local Distribution 6
1.2.2 Available Ground Measurements in Libya 8
List of Tables
Table 1-1: Sites pre-selected for solar plants
Table 1-2: Summary of wind data review
Table 1-3: Summary of pre-selected sites according to solar and wind resource
List of Figures
Figure 1-1: Satellite view (left) and topography (right) of Libya, source: Solar-Med-Atlas
Figure 1-2: GHI map from the Solar-Med-Atlas (left) and World Bank’s ESMAP Global Solar Atlas
(right)
Figure 1-3: DNI map from the Solar-Med-Atlas (left) and World Bank’s ESMAP Global Solar Atlas
(right)
Figure 1-4: Locations selected for solar power plants incl. solar met stations
Figure 1-5: Wind energy density at 100m above ground level - DTU Global Wind Atlas
Figure 1-6: Average annual wind speed at 100 m above ground level – DTU Global Wind Atlas
Figure 1-7: Wind energy density in Libya, North-western coast - DTU Global Wind Atlas
Figure 1-8: Wind energy density in Libya, North-eastern coast - DTU Global Wind Atlas
Figure 1-9: Wind energy density in Libya - DTU Global Wind Atlas
Figure 1-10: Wind profile illustration of low level jets - Source: NREL
Figure 1-11: Locations with available ground wind data
Libya SPREL – LCEP Report – Annex I – Solar and Wind Resource
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Abbreviations CAPEX Capital Expenditures
CCGT Combined Cycle Gas Turbine
CRS/CR Central Receiver System
CSP Concentrating Solar Power
DNI Direct Normal Irradiation
DSG Direct Steam Generation
ENTSO European Network of Transmission System Operators
ESS Energy Storage System
FLH Full Load Hours
GECOL General Electric Company of Libya
GHI Global Horizontal Irradiation
GI Global Irradiation
GT Gas Turbine
HFO Heavy Fuel Oil
HRSG Heat Recovery Steam Generator
HTF Heat Transfer Fluid
IDC Interest During Construction
IEC International Electro-chemical Commission
IGBT Insulated Gate Bipolar Transistor
IPP Independent Power Producer
IRR Internal Rate of Return
ISCC Integrated Solar Combined Cycle
ITRPV International Technology Roadmap for Photovoltaic
LCEP Least Cost Expansion Plan
LCoE Levelized Cost of Electricity
LDS Long-Duration Energy Storage
LFO Light Fuel Oil
LID Light Induced Degradation
LLJ Low Level Jet
LVRT Low Voltage Ride Through
OPEX Operational Expenditures
PID Potential Induced Degradation
PPA Power Purchase Agreement
PSP Private Sector Participation
PT Parabolic Trough
PV Photovoltaics
RE Renewable Energies
REAOL Renewable Energy Authority of Libya
SCA Solar Collector Arrangement
SCGT Simple Cycle Gas Turbine
SM Solar Multiple
STATCOM Static Compensators
SPREL Strategic Plan for Renewable Energies in Libya
TES Thermal Energy Storage
TMY Typical Meteorological Year
TSC Thyristor Switched Capacitors
WACC Weighted Average Capital Cost
WB World Bank
WTG Wind Turbine Generator
- 1 -
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1. Solar and Wind Resource
Based on the information made available and the Consultant databases the Consultant reviewed the
overall solar and wind resources available in the country and identified the most suitable areas, and
when possible sites, of the country for implementation of PV, wind or CSP projects. The main activities
include:
Review of available satellite wind and solar data for the complete country;
Determination of the sites where measurement campaigns have been carried out;
Determination of the sites with ground meteorological data;
Appraisal of the completeness, quality and plausibility of the meteorological data provided; and
Determination of the extent to which the meteorological data provided can be used (e.g. for LCEP,
for feasibility study or bankability).
1.1 Solar Resource
Libya has a high potential of solar energy for both, PV-technology and CSP-technology due to the very
favourable conditions of global and direct solar radiation for almost the whole country. The annual av-
erage of sunshine hours reaches around 3,200 hours.
Libya is fourth in size among the countries of Africa and seventeenth among the countries of the
world. The Mediterranean coast and the Sahara Desert are the country's most prominent natural fea-
tures. As can be seen in Figure 1-1, Libya is dominated by arid and warm desert. There are several
highlands but no true mountain ranges except in the largely empty southern desert near the Chadian
border.
In general, intensity of GHI and in special DNI is strongly related to the ground elevation that can be
seen by comparison of the topography map in Figure 1-1 with the GHI/DNI maps in Figure 1-2 and
Figure 1-3.
Figure 1-1: Satellite view (left) and topography (right) of Libya, source: Solar-Med-Atlas
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1.1.1 Global Horizontal Irradiance (GHI) - PV
The distribution of the long-term annual GHI sums is quite homogeneous in Libya and can reach up to
around 2,500 kWh/m2 for the Tibesti Massif in the South that rises to over 2,200 metres. However, this
region is very hard accessible and an almost total empty desert countryside, thus not the first option
for solar energy.
The most part of Libya reaches annual GHI sum between 2,100 kWh/m2 and 2,300 kWh/m
2 as can be
seen in Figure 1-2, which shows the GHI maps from two different sources: the Solar-Med-Atlas (left)
and World Bank’s ESMAP Global Solar Atlas (right). Since the Solar-Med-Atlas just covers the Medi-
terranean region the used colour code reaches from around 1400 kWh/m2 up to around
2600 kWh/m2. Thus, the GHI of the Solar-Med-Atlas is visualized with a higher resolution in compari-
son to the World Bank’s ESMAP Global Solar Atlas, which covers nearly the complete planet using a
colour code reaching from around 600 kWh/m2 up to around 2700 kWh/m2. Therefore, the correlation of GHI to the ground elevation could be better seen in the Solar-Med-Atlas.
In general, almost the whole country reaches long-term annual GHI sums, which are more than suita-
ble for solar energy applications with PV-technology. Higher GHI values occur in the centre, South,
Southeast and West (yellow, orange and red colour shades in Solar-Med-Atlas, Figure 1-2). Lower
GHI values of around 2,000 kWh/m2 appear in the North and in Northeast (green colour shades in So-
lar-Med-Atlas, Figure 1-2). In the coastline, it is partly below, especially in the eastern and southern
part of the Gulf of Sirte. Only the Solar-Med-Atlas shows for very small areas long-term annual GHI
sums below 1,900 kWh/m2 indicated by the blue colour shades.
Figure 1-2: GHI map from the Solar-Med-Atlas (left) and World Bank’s ESMAP Global Solar At-
las (right)
1.1.2 Direct Normal Irradiance (DNI) - CSP
In comparison to the GHI distribution the distribution of the long-term annual DNI sums is naturally
more heterogeneous in Libya, as can be seen in Figure 1-3, which shows the DNI maps from the So-
lar-Med-Atlas (left) and World Bank’s ESMAP Global Solar Atlas (right). The highest values up to
around 3,000 kWh/m2 can also be found for the Tibesti Massif in the South. However, this region is
very hard accessible and an almost total empty desert countryside, thus no option for solar energy.
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In a big part of the country the long-term annual DNI sums, lying between 2,200 kWh/m2 and 2,500
kWh/m2, are suitable for solar energy applications with CSP-technology. Similar to the GHI distribu-
tion, higher DNI values occur in the centre, South, Southeast and West (yellow, orange and red colour
shades in Solar-Med-Atlas, Figure 1-3). Lower DNI values of around 2,000 kWh/m2 to 2,200 kWh/m
2
appear in the North, Northeast and Southwest (green colour shades in Solar-Med-Atlas, Figure 1-3).
In the coastline it is partly below, especially in the eastern and southern part of the Gulf of Sirte. Only
the Solar-Med-Atlas shows for very small areas long-term annual DNI sums below 1,900 kWh/m2 indi-
cated by the blue colour shades.
Figure 1-3: DNI map from the Solar-Med-Atlas (left) and World Bank’s ESMAP Global Solar At-
las (right)
1.1.2.1 Available ground solar measurements in Libya
The climatological long-term annual average solar irradiance is usually the most crucial information for
site selection and project implementation. Solar resource assessments aim to get long-term averages
of the GHI for PV projects or DNI for CSP projects. These data typically represent the long-term annu-
al average P50 (i.e. with a probability of exceedance of 50% in all cases and is presented on a data
set called Typical Meteorological Year (TMY), which shall closely represent P50 values.
One of the main aims of a solar resource assessment is to prepare a TMY data set, which should also
include auxiliary meteorological parameters like ambient temperature, humidity, and wind speed and
wind direction. This TMY is the base for site-specific engineering and yield estimation. Having suffi-
cient and proper ground measurements allows for more accurate long-term averages and hence more
accurate TMYs.
According to the information made available to the Consultant and direct requests of the stakeholders
the following locations are pre-selected for studying the solar resource potential available in Libya:
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Table 1-1: Sites pre-selected for solar plants
Site Remarks
Jadu (Bir al-Ganam) GHI and DNI ground measurements available
Ghadamis GHI and DNI ground measurements available
Edri GHI ground measurements available
Thala GHI ground measurements available
Sebah GHI and DNI report available; no ground measurements available
Shahat GHI Report available; no ground measurements available
Hun GHI Report available; no ground measurements available
Brega Suggested by Consultant; only satellite data
Zliten Suggested by REAOL; only satellite data
Jagboub Suggested by GECOL; only satellite data
Kufra1 Suggested by GECOL; only satellite data
Kufra2 Suggested by GECOL; only satellite data
According to Table 1-1 although many resource campaigns for solar ground measurements were
commissioned the bulk of the ground data is missing and cannot be retrieved. The best sets for solar
data are at Bir Al-Gahnam, Ghadamis, Edri and Thala, however only Bir Al-Gahnam and Ghadamis
with DNI data. Although for some of the remaining sites there are solar resource assessment reports
the ground data is missing and thus only satellite data could be used for the simulations.
Brega, Zliten, Jagboub, Kufra1 and Kufra2 were added to the analyses either by the Consultant or by
suggestion of the stakeholders. Data to be used at these sites is also satellite data.
The locations at the coastal areas are characterized by significant lower long-term averages for GHI
and DNI in comparison to the other locations. This is especially critical for DNI, which strongly de-
pends on aerosols and water vapour present in higher quantities in the atmosphere of coastal areas.
Therefore these areas will not be considered for solar application as part of the LCEP.
The conclusions are as follows.
For the locations where ground measurements of GHI and DNI are available the uncertainty of the
corresponding long-term best estimates could be significantly reduced by considering these on-site
measurements.
For following locations ground measurements are already available to us:
– Ghadamis;
– Bir Al-Ghanam;
– Edri; and
– Thala
For following locations ground measurements exist but data sets are missing:
– Hun;
– Sebah; and
– Shahat.
Table 1-3 presents a summary of the pre-selected sites for verification of the solar resource after per-
forming a review of the solar data provided and, when relevant, gives an overview of the long-term es-
timate of GHI and DNI for the considered locations.
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Figure 1-4 shows the locations for solar power plants considered for the LCEP including those with
available ground data and those with only satellite. Ground data will be used for reducing uncertainties
in these areas.
It is important to note again that DNI ground data is only available at Bir Al-Gahnam and Ghadamis
and that satellite derived DNI carries along much higher uncertainties than satellite derived GHI.
Figure 1-4: Locations selected for solar power plants incl. solar met stations
1.2 Wind Resource
Libya has very good potential for onshore wind. In terms of wind energy density1, Libya is predicted to
have higher onshore wind resource than northern countries where wind power is widely spread, such
as Germany and Spain. In addition, the wind resource is similar to other countries in the region where
wind power is experiencing rapid development, such as Egypt and Jordan.
1 Wind energy density is the average power available per square meter of swept area of a turbine. It is a far more reliable indi-
cator than the average annual wind speed, as it takes into account the wind distribution, the temperature, humidity and pressure of the wind.
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Figure 1-5: Wind energy density at 100m above ground level - DTU Global Wind Atlas
Figure 1-6: Average annual wind speed at 100 m above ground level – DTU Global Wind Atlas
1.2.1 Wind Resource – Local Distribution
Along the northern coast, the wind resource is high. Around the cities of Misurata, Sirte, and Tripoli,
the wind resource ranges between 400-450 W/m2. The plateau south of Alaluas, and the coastal area
to the west and south-east of Misurata show interesting potential.
While sea areas seem darker, the wind potential is equal or higher than in the coast. This effect is due
to the background sea colour in the map, which makes those areas appear slightly darker.
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Figure 1-7: Wind energy density in Libya, North-western coast - DTU Global Wind Atlas
In the north-eastern coast, the woodland areas of Jebel Akhdar (al-Jabal al-Akhdar) show reduced
wind resource (250-300 W/m2). However, the plateau to the south shows very good wind resource
(450-500 W/m2).
Figure 1-8: Wind energy density in Libya, North-eastern coast - DTU Global Wind Atlas
In the mainland, the most promising areas are the Nafusah Plateau and the Murzuq plateau.
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Figure 1-9: Wind energy density in Libya - DTU Global Wind Atlas
1.2.2 Available Ground Measurements in Libya
A wind measurement campaign can be carried out for several purposes, such as climate research,
wind atlas elaboration, and/or wind farm development. Depending on the case, different standards and
methodologies are to be applied to obtain the required data. For the purposes of the LCEP wind data
provided has been surveyed taking as a reference the MEASNET guidelines, the gold standard for
wind measurement campaigns for wind farm development.
When developing a wind farm, the wind measurement campaign and wind resource assessment are
the most important aspects since they are the basis to calculate the energy production of the wind
farm and the revenues that the wind farm will produce. A proper and state-of-the-art measurement
campaign and resource assessment will yield lower uncertainties in the energy yield.
A bankable wind resource assessment is one in which high quality verifiable data is available to quan-
tify the uncertainty in wind resource at the planned wind project location. The key to this assessment is
the data obtained by the wind measurement campaign.
The gold standard for wind measurement campaigns are the MEASNET guidelines, based on IEC,
ISO, and IEA standards. Full compliance with MEASNET standards is required for a high quality,
bankable wind resource assessment.
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The complete list of MEASNET requirements can be found online at:
http://www.measnet.com/wp-content/uploads/2016/05/Measnet_SiteAssessment_V2.0.pdf
Since it is a 56-page document, and freely available online, it is considered too lengthy to be included
in the present document. However, the following requirements are key to justify the analysis of the
wind data for the purposes of the LCEP:
The height of the primary wind speed measurement level shall be at least 2/3 of the planned hub
height (Section 6.4, third paragraph);
In case of changes of sensors, complete documentation of performed work, changes in equipment
and resulting changes of calibration values (Annex A, “Measurement history” bullet point); and
For mast measurements: Unambiguous assignment of the data channels to the sensors (Annex A,
“Measurement data” bullet point).
Wind data was provided by REAOL for 28 measurement sites. Only 6 sites out of the 28 were provid-
ed with a wind measurement report:
Dernah,
Azizyah,
Assaba,
Gotria / Goterria,
Misallatah, and
Tarhuna.
For estimating the production at these sites, the data can be regarded as acceptable. The Consultant
has interpreted the data files based on previous experiences; the signals have been identified (wind
speed, wind direction, temperature, pressure, humidity) but information regarding their height and lo-
cation on the mast is missing. However, combined with virtual met-mast data from NASA (MERRA 2
database), the production of wind farms can be modelled with a reasonable level of accuracy (uncer-
tainty levels above 20% are considered acceptable for the LCEP purpose).
It is important to highlight that the available reports are not bankable wind resource assessment ac-
cording to MEASNET guidelines. Therefore, a bankable feasibility study cannot be performed with the
current data.
Where no measurement report has been provided, no further analysis could be performed with suffi-
cient certainty (22 out of 28 sites). The signals in the measurement data files are not by themselves
sufficient. In addition, the files themselves do not have information regarding the met mast position
neither identification of the mast configuration was possible. It is necessary to clarify the sensors and
height of installation, the logger channel to which they are connected and sensors’ model, amongst
others, as this cannot be deducted out of the information provided.
The data currently available is not suited for utility-scale wind power development involving debt fi-
nancing. The available reports are not bankable according to MEASNET guidelines, due to a number
of deficiencies (see Table 1-2). Worth highlighting is that the maximum measurement height (40 m) is
not compatible with today’s state of the art utility scale wind turbines (minimum of 80 m hub height).
For the development of future wind farms, the Consultant recommends performing new wind meas-
urement campaigns compliant with MEASNET guidelines in their latest version, or equivalent stand-
ards.
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The maximum height of the analysed data (available) is 40 m, which does not allow identifying if Low
Level Jets (LLJs) are common at the sites. A LLJ is a phenomenon starting usually at dusk. When the
ground has cooled down, the turbulent, well-mixed, boundary layer comes to rest after the turbulence
production by solar irradiation and thermal mixing vanishes. In practice, it causes increased wind
speed at high heights at night, and thus increased production for wind turbines.
The height to the maximum wind speed in a LLJ is typically 200 m; however, this is greatly dependent
on the local conditions. The LLJ region of interest for wind power production ranges from 40 to 260 m.
WTGs with an upper tip height below 40 m receive negligible impact from LLJs.
Figure 1-10: Wind profile illustration of low level jets - Source: NREL
The wind measurement data and reports analysed are summarized in Table 1-2 below.
The conclusions are as follows:
In 22 of the 28 measurement sites, the wind resource assessment reports and logs are missing.
The raw data cannot be interpreted without these reports hindering further analyses.
For the six sites that have wind resource assessment reports:
– For Dernah site (MTorres report # EE20100222)
♦ The uncertainties have not been analysed;
♦ Measurement documentation is severely incomplete; and
♦ Site assessment is incomplete.
– For the rest of the sites (ambio reports)
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♦ The received reports are severely incomplete, according to the MEASNET guidelines;
♦ Measurement documentation is severely incomplete;
♦ Measurement data is incomplete;
♦ Site assessment is incomplete; and
♦ The logger channel assignment is not defined.
– The maximum measurement height of all of the above is 40 m above ground level. This does
not allow to identify LLJs, and thus can lead to underestimations of the wind energy yield.
None of the wind measurement campaigns can be termed bankable according to the MEASNET
guidelines with the current information. Therefore, it is not possible to base a bankable feasibility study
on this data.
Table 1-2 shows a summary of the wind measurement systems in Libya with the main data and out-
comes of data review. Figure 1-11 show the location of those wind masts with suitable wind data for
further analyses. Although, as mentioned previously in this section, ground data is not bankable, the
data available on those areas features indicates optimum wind resource and proper infrastructure for
installation of a wind park.
Figure 1-11: Locations with available ground wind data
Alternatively, areas close to Brega and Hun could be considered for installation of wind power. Other
locations in the south e.g. Sebah, although with still good wind resource will be badly affected by
abrasion and curtailment of wind energy due to high temperatures and thus are not recommended for
the first years of the LCEP.
For the reasons above the sites considered for wind development in the LCEP are:
Aziziya;
Misallatha;
Misurata;
Assaba;
Derna;
Al Maqron; and
Brega.
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Table 1-2: Summary of wind data review
Area Site Lat (N) Long (E) Max height
(m)
Annual av-erage wind
speed at max height
2
(m/s)
Report Is the report
MEASNET compliant?
Measure-ment data available?
Other
Coastal Area Al Maqrun
31.263485
20.83294 40 No No Yes Sensor information provided in a separate email
Coastal Area Dernah 32.710684 22.753885 40 7.96 Yes No Yes
Additional information: P.E.A & Wind Farm Report. Datalogger channel assignation Wind Farm Report does not match the data in measurement file - An interpretation has been made, but we cannot ensure its accuracy.
Coastal Area Misurata / Misrata
32.103202
15.174009
40 No No Yes Sensor information is missing – Data cannot be interpreted
Coastal Area Sirt 31.92155
16.335073
40 No No Yes Sensor information is missing – Data cannot be interpreted
Coastal Area Tolmeita /Tolmetha
32.415506
20.55581 40 No No Yes Sensor information is missing – Data cannot be interpreted
Arabic region Azia / Aziziya 32.33106 13.051861 40 7.35 Yes No Yes No data on channel configuration on final report - Logger data cannot be interpreted 100%
Arabic region Assaba / Asba / Sabha 32.12213 12.87776 40 6.35 Yes No Yes No data on channel configuration on final report - Logger data cannot be interpreted 100%
Arabic region Goterria / Gtri / Gotria 32.03832 13.07304 40 5.56 Yes No No No data, only final report, no data on channel configuration
Arabic region Misalatah 32.611444 13.859514 40 6.68 Yes No Yes No data on channel configuration on final report - Logger data cannot be interpreted 100%
Arabic region Tarhuna / Tarh 32.43515 13.56144 40 7.14 Yes No Yes No data on channel configuration on final report - Logger data cannot be interpreted 100%
South East Abugrin - ق وزري No No Yes No data on channel configuration - Logger data cannot be interpreted 100% 60 22.11013 25.40762 اب
South East Al Sarir - ر سري No No Yes Sensor information is missing – Data cannot be interpreted 60 21.39861 27.15984 ال
South East Lijkhira- 60 21.41264 29.18981 اجخرة No No Yes Sensor information is missing – Data cannot be interpreted
South East
Al Tariq al Sahrawi - ق طري صحراوي ال ال
30.24108 20.32382 60 No No Yes Sensor information is missing – Data cannot be interpreted
South East Al Kafara - فرة ك No No Yes Sensor information is missing – Data cannot be interpreted 60 23.17545 24.3174 ال
South East Tazerbo - و ازرب No No Yes Sensor information is missing – Data cannot be interpreted 60 21.55348 26.1695 ت
South East Marwa - 60 21.27329 32.26509 مراوة No No Yes Sensor information is missing – Data cannot be interpreted
South East Gagboob 29.46731 24.22072 60 No No Yes Sensor information is missing – Data cannot be interpreted
South East Ghkra 24.3174 23.17545 60 No No Yes Sensor information is missing – Data cannot be interpreted
South East Argeba 26.34456 13.3358 60 No No Yes Sensor information is missing – Data cannot be interpreted
South West Bongeam 23.253 15.24479 60 No No Yes Sensor information is missing – Data cannot be interpreted
South West Qatron / Gatroon 24.51101 14.34186 60 No No Yes Sensor information is missing – Data cannot be interpreted
South West Gath 25.02261 10.10264 60 No No Yes Sensor information is missing – Data cannot be interpreted
South West Hoon 29.07311
15.530893
60 No No Yes Sensor information is missing – Data cannot be interpreted
South West Schwerf 29.59368 14.14007 60 No No Yes Sensor information is missing – Data cannot be interpreted
South West Sabha 26.48333
14.262009
60 No No Yes Sensor information is missing – Data cannot be interpreted
South West
Tragen / Traghan/ Taraghin
25.57552 14.30349 60 No No Yes Sensor information is missing – Data cannot be interpreted
South West Abugrin - ق وزري No No Yes Sensor information is missing – Data cannot be interpreted 60 22.11013 25.40762 اب
2 According to the wind resource assessment report
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It is important to note that Al Maqrun configuration of the anemometers in the tower was provided via
email by REAOL during the preparation of the LCEP. Furthermore, Brega site was suggested by
REAOL.
In general, and to reduce the complexity of the LCEP model the Consultant will, if necessary, select
representative areas for wind farms at the sites selected i.e. for sites nearby with similar wind potential
according to satellite data one site could be considered representative of the area.
Table 1-3 summarizes the locations selected and the corresponding measurement coordinates for the
resource analyses to be used for the site selection and the later simulations of the technology configu-
rations part of the LCEP.
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Table 1-3: Summary of pre-selected sites according to solar and wind resource
Meteorologi-cal station
Area City/town Coordinates (Latitude, longitude)
Name Coordinates (Latitude, longitude)
Distance (km) Type Mast height (m)
Wind speed (m/s)
Wind Ground data
GHI1 kWh/m2/
y
GHI Ground da-
ta
DNI1 kWh/m2/
y
DNI Ground
data
Tripoli Aziziya 32°19'52"N; 13° 3'7"E Aziziya 32°19'51.82"N; 13° 3'6.70"E 0 WIND 40 7,35 Report/data wo sensor
1986 2028
Tripoli Misal-latha
32°38'59"N; 13°53'27"E Misal-latha
32°36'41.20"N; 13°51'34.25"E 0 WIND 40 6,68 Report/data wo sensor
1956 1993
Tripoli Misurata 32°28'7"N; 14°48'47"E Misurata 32° 6'11.53"N; 15°10'26.43"E 60 WIND 40 Data wo sensor 1925 1850
Tripoli Assaba 32° 7'20"N; 12°52'40"E Assaba 32° 7'19.67"N; 12°52'39.94"E 0 WIND 40 6,35 Report/data wo sensor
Tripoli Zliten 32°12'37"N; 14°30'1"E satellite data GHI Satellite
Tripoli Jadu 32° 5'55"N; 12° 4'47"E Bir al Gahnam
32° 21' 3.19" N; 12° 39' 21.39" E 60 GHI/DNI 1987 Data 2023 Data
Bengazhi Derna 32°42'37"N; 22°45'14"E Derna 32°42'38.46"N; 22°45'13.99"E 0 WIND 40 8 Report/data 1917 1821
Bengazhi Al Maqron
31°15'48"N; 20°49'59"E Al Maqron
31°15'48.55"N; 20°49'58.58"E 0 WIND 40 Data
Bengazhi Al Tamimi 32°27'2"N; 23° 5'28"E satellite data GHI 2004 Satellite 1999
Bengazhi Shahat 32°48'37"N; 21°44'16"E Shahat 32°45'36.00"N; 21°53'24.00"E 15 GHI Report
Sebah Sebah 26°47'20"N; 14°25'16"E Sebah 26°47'19.65"N; 14°25'16.22"E 4 GHI/DNI 60 Data wo sensor 2248 Report 2259 Report
Sebah Edri 27°29'19"N; 13°10'50"E Argiba 26°34'50.28"N; 13°34'25.56"E 100 GHI Data
Ghad-amis
Ghadamis 30° 5'35"N; 9°36'17"E Ghadamis 30°10'4.80"N; 9°45'21.60"E 17 GHI/DNI 2127 Da-ta/Report
2162 Data
Brega Brega 30°23'37"N; 18°41'56"E satellite data _WIND Satellite
Hun Hun 29° 8'34"N; 15°51'34"E Hun 29° 9'15.69"N; 16° 0'17.60"E 15 GHI 60 Data wo sensor 2157 Report 2212
Ghat Thala 25°24'37"N; 10°21'34"E Ghat 24°57'51.53"N; 10°10'32.72"E 52 GHI 60 Data wo sensor Data
Jagboub Jagboub 29°44'28"N; 24°30'0"E satellite data GHI Satellite
Jagboub Kufra1 27°38'53"N; 21°42'47"E satellite data GHI Satellite
Jagboub Kufra2 26°56'49"N; 22° 9'3"E satellite data GHI Satellite
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Libya - Supporting Electricity Sector Reform (P154606)
Contract No. 7181909 - Task D: Strategic Plan for Renewable Energy Development
Least Cost Expansion Plan Report Annex II – Grid Connection Aspects 12 December 2017
Client:
The World Bank
1818 H Street, N.W.
Washington, DC 20433
Consultant:
GOPA-International Energy Consultants GmbH
Justus-von-Liebig-Str. 1, 61352 Bad Homburg, Germany
Phone: +49-6172-1791-800; Fax: +49-6172-944 95 20
eMail: info@gopa-intec.de; www.gopa-intec.de
Suntrace GmbH
Grosse Elbstrasse 145c, 22767 Hamburg, Germany
Phone: +49-40-767 96 38 0; Fax: +49-40-767 96 38 20
www.suntrace.de
Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects
LBY2560_TaskD_ StageI_LCEP_Report_AnnexII_GridConnection.docx
Table of Contents Page
1. Grid Support Overview 3
1.1.1 PV 3
1.1.2 Wind 4
1.1.3 CSP 5
1.1.4 General Notes on Grid Support with RE 6
2. Grid Connection Alternatives 8
2.1 Transmission System Network Studies 9
2.2 Connection Points for Sites Suggested by Stakeholders 12
2.3 Conclusions on Grid Connection Alternatives 12
List of Tables
Table 1-1: Stability criteria according to ENTSO – Levels according to Consultant
Table 2-1: Summary of identified connection points – Transmission system network studies
Table 2-2: Substations identified for sites suggested by stakeholders
List of Figures
Figure 2-1: Georeferenced Libyan grid as provided by GECOL
Figure 2-2: Potential connection points for RE facilities in Libya acc. to transmission studies
Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects
LBY2560_TaskD_ StageI_LCEP_Report_AnnexII_GridConnection.docx
Abbreviations CAPEX Capital Expenditures
CCGT Combined Cycle Gas Turbine
CRS/CR Central Receiver System
CSP Concentrating Solar Power
DNI Direct Normal Irradiation
DSG Direct Steam Generation
ENTSO European Network of Transmission System Operators
ESS Energy Storage System
FLH Full Load Hours
GECOL General Electric Company of Libya
GHI Global Horizontal Irradiation
GI Global Irradiation
GT Gas Turbine
HFO Heavy Fuel Oil
HRSG Heat Recovery Steam Generator
HTF Heat Transfer Fluid
IDC Interest During Construction
IEC International Electro-chemical Commission
IGBT Insulated Gate Bipolar Transistor
IPP Independent Power Producer
IRR Internal Rate of Return
ISCC Integrated Solar Combined Cycle
ITRPV International Technology Roadmap for Photovoltaic
LCEP Least Cost Expansion Plan
LCoE Levelized Cost of Electricity
LDS Long-Duration Energy Storage
LFO Light Fuel Oil
LID Light Induced Degradation
LLJ Low Level Jet
LVRT Low Voltage Ride Through
OPEX Operational Expenditures
PID Potential Induced Degradation
PPA Power Purchase Agreement
PSP Private Sector Participation
PT Parabolic Trough
PV Photovoltaics
RE Renewable Energies
REAOL Renewable Energy Authority of Libya
SCA Solar Collector Arrangement
SCGT Simple Cycle Gas Turbine
SM Solar Multiple
STATCOM Static Compensators
SPREL Strategic Plan for Renewable Energies in Libya
TES Thermal Energy Storage
TMY Typical Meteorological Year
TSC Thyristor Switched Capacitors
WACC Weighted Average Capital Cost
WB World Bank
WTG Wind Turbine Generator
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1. Grid Support Overview
This section is an overview of solar and wind alternatives and its grid connection aspects relevant to
grid support. Further, this section focuses on probable impact of penetration of renewable sources by
different technologies on the Libyan electric grid in terms of system performance, technical challenges
and opportunities for achieving higher levels of reliability and efficiency in the grid performance.
Note: The content of this section deals with qualitative characteristics of grid support in order to high-
light how RE nowadays could provide grid support in a general manner. This assignment, and for ex-
tension, this section does not deal with analyses of power networks. Due to its complexity, such anal-
yses if required shall be part of a separate assignment or shall be carried out during the implementa-
tion of the LCEP.
1.1.1 PV
One of the key components of PV systems is the inverter. DC (Direct Current) output from PV system
is changed into AC (Alternating Current) by the inverters. The performance of the inverter is especially
important for grid connected PV plants since it directly influences whether the PV power plant can
meet the requirements of the grid operation. Nowadays, most of the inverters have LVRT capability
(Low Voltage Ride Through) and flexible active and reactive power control capabilities. However,
since there is no rotating component, PV systems cannot supply inertia support to the power system
/grid.
As also mentioned by GECOL PV can support voltage control when located at the end of long trans-
mission lines.
Inverters are smart enough to help solar power plant to get along with the grid. In addition, to convert-
ing DC to AC they also enable monitoring, decision making and control functions. Due to this feature,
the PV system currently brings more support to existing networks. Further, most larger inverters con-
trolling its own output, they provide reactive power support to the grid as and when needed. This in-
deed improves grid stability. The basic grid support functions are mentioned as below:
Active Power Curtailment: The adjustment of active power in various response time frames assists
in balancing the generation and load, thereby improving power system reliability. When solar pro-
duces too much (as established by grid operators), the inverter increases PV voltage to reduce the
power output of the array.
Reactive power control: When voltage and current are not in-phase, you get reactive power that
moves back and forth in the grid. This power can help grid operators regulate voltage on a
timeframe of hours or days. Through SCADA systems, utilities can tell the inverter how much reac-
tive power should get into the grid.
Power factor control: Inverters can set the ratio of reactive power to active power, on a cycle to cy-
cle of the AC line, which help maintain voltage.
Voltage ride-through: The Inverter can help maintain solar plant operation through periods of lower
grid voltage to avoid disconnection, which may cause a chain reaction of other plants disconnecting
due to the dip in voltage, known as cascading. This helps keep the grid stable.
Frequency ride-through: The inverter can help keep the solar plant from disconnecting from the grid
during time of high or low variations in frequency, determined by regulatory requirements, therefore
aiding grid stability.
Ramp-rate controls: The inverter can control the rate at which it transitions between different estab-
lished power factor points. This ensures the plant output does not ramp up or down faster than a
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specified limit. Energy storage technology can add or subtract power to or from the PV output to
smooth out the high frequency components of the PV power.
1.1.2 Wind
There are mainly four types of WTGs commercially in operation. Each type has some unique charac-
teristics due to its features in the aspects of grid support.
Type 1 – Fixed speed Induction Generator: This type of WTG operates on fixed speed, thus their
output fluctuates as wind speed varies. To alleviate this problem, stall control system is needed.
Because induction generators absorb a lot of reactive power when generating active power, type 1
WTG requires reactive power compensators. This type of WTGs has no reactive power control ca-
pability. The devices like TSCs (Thyristor switched capacitors), STATCOMs (Static Compensators)
are needed in the system to provide reactive power control. There is high risk involved of dynamic
voltage collapse with WTG of type 1. Therefore, in the voltage dip scenario, this type of WTG need
to disconnect from operation.
Type 2: Induction Generator with Variable Rotor Resistance: This type of WTG allows speed varia-
tion of 10%, which improves power quality and reduces mechanical loading of turbine components.
This type of WTG equips with induction generator and it requires compensators for reactive power
compensation. However, there is no reactive power capability available in this type of generators;
therefore TSCs and STATCOM have to be added additionally. Further, it has limited LVRT , thus in
case of voltage collapse mitigation measures can be taken by either providing fast increase of rotor
resistance during faults or by increasing reactive power compensation devices in the system.
Type 3 Double Fed Induction Generator: This type of WTG combines the advantages of previous
two types design with advance power electronics (type 1 and type 2). The rotor of this WTG is con-
nected to the grid through a back to back insulated gate bipolar transistor (IGBT) that controls both
magnitude and frequency of the rotor current. Further, it provides the advanced concept for varia-
ble speed operation. The converter provides decoupled control of active and reactive power, ena-
bling flexible voltage control without additional reactive power compensation, as well as fast voltage
recovery and voltage ride through. In case of severe faults, crowbar protection may be needed.
There is no reactive power control available when crowbar is connected.
Type 4 Generator with fully rated converter/ direct drive: In this type of WTG, the stator of the gen-
erator is connected to the grid via full power back to back IGBT power converter, which means all
the power output goes to the grid through the converter. The generator may be a synchronous
generator with wound rotors or induction generator. The gear box may be drive-train type, half di-
rect drive or direct drive (no gearbox). A type 4 WTG is completely decoupled from its grid, thus it
can provide even wider range of speed variation as well as reactive power and voltage control ca-
pability. In addition, its output can be modulated to zero, thereby limiting the short circuit contribu-
tion to the grid. This type of WTG also provides reactive power at zero active power (STATCOM
mode). The synchronous generators released their stored kinetic energy into the grid, reducing the
initial rate of change of frequency and allowing slower governor actions to catch up and contribute
frequency stabilization. Therefore, a performance similar to conventional generators can be
achieved with wind power plant by utilizing a controlled inertial response.
Early versions of the turbine generators (type 1) consisted of fixed-speed wind turbines with conven-
tional induction generators. This type of machines is limited to operation in narrow wind-speed range.
In addition, the conventional induction generator (type 2), which is directly connected to the grid, re-
quired the reactive power support be provided (locally) to achieve desired voltage level. The highly ef-
ficient, variable speed DFIG (Double Fed Induction Generator) (type 3) is designed to extract maxi-
mum energy from the wind, and it puts out the electricity at a constant frequency irrespective of speed.
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The generators with fully rated converters (type 4) which have synchronous generators and fully rated
converters have a wide range of both real and reactive power for varying wind speeds.
A WTG has flickers which will highly impact on the power quality of the system. Further, by looking the
Libyan grid stability and reliability aspects, type 1, 2 and 3 WTGs may not be recommended. Type 4
WTG is the most recommended as it will support the behaviour of the Libyan electric grid. However,
type 4 still might have a limited number of suppliers mostly for the climatic conditions of Libya and
therefore due to market conditions at least type 3 and type 4 are to be considered for procurement and
competition purposes.
1.1.3 CSP
CSP technologies deliver electricity to the grid by means of a steam turbine and a conventional elec-
trical generator. In general, CSP without storage features many grid advantages for the grid as con-
ventional thermal power plants such as inertia, however with also many disadvantages including fluc-
tuations and no possibility of operation through the night. In particular, the real advantage of CSP
plants relies in its thermal storage capability for many hours and in capacities in the order of tens or
even hundreds of megawatts. For the purpose of this assignment, only CSP with storage will be fur-
ther analysed as it can be considered as the benchmark of solar and wind technologies in what refers
to grid support.
Utilizing the stored thermal energy to operate a conventional synchronous generator, they can also
support power quality and provide ancillary service, including voltage support, frequency response,
regulation and spinning reserves, as well as ramping services.
When comparing CSP with thermal energy storage to alternative renewable technologies (including
CSP without storage), there are several primary categories of additional benefits provided by thermal
energy storage as listed below:
Energy
– Hourly optimization of energy schedule;
– Sub-hourly energy dispatch; and
– Ramping reserves.
Ancillary Services (for secondary frequency control)
– Regulation;
– 10- minute spinning reserves; and
– Operating reserves on greater than 10 minute time-frames synchronized generator.
Power quality and other ancillary services
– Voltage Control;
– Frequency response; and
– Black-start.
Capacity
– Generic MW shifted to meet evolving system needs; and
– Operational attributes.
Integration and curtailment cost compared to solar PV and Wind
– Reduced production forecast error and associated reserve requirements;
– Reduced curtailment due to greater dispatch flexibility without production losses; and
– Ramp mitigation.
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1.1.4 General Notes on Grid Support with RE
Integrating RE in a power system shall, to the extent possible, not pose a conflict with a “robust, relia-
ble and stable” supply of electricity. Grid support of solar and wind technologies will be at this stage
only qualitatively evaluated. Low penetration of renewable energies (i.e. low share of RE or single digit
percentages) will need to prioritize the following technical requirements1:
Protection;
Power quality;
Power reduction during over-frequency;
Communication;
Adjustable reactive power; and
Constraining active power (active power management).
Increasing the penetration of RE to higher shares up to 20%, will require additionally2:
LVRT including current contribution; and
Simulation models.
Following IRENA’s recommendations for these shares the following generators will be recommended:
Synchronous machines;
PV converters;
Wind turbines with full converter (type 4); and
Wind turbines with DFIG (type 3)
Depending on the progress and success of the implementation of the LCEP, it is recommended to re-
visit the LCEP timely before of 2025 and perform network analyses for the additions of capacity until
2030.
Alternatively, to IRENA’s guide and only for illustrative purposes, Table 1-1 shows stability criteria ac-
cording to the European Network of Transmission System Operators (ENTSO). With the bars, the
Consultant intends to show the level of support of solar and wind technologies to the grid (green posi-
tive support, red negative support and white no support). Note that this is only indicative and reliable
results can only be obtained with a proper network analysis.
1 Scaling up Variable Renewable Power: The Role of Grid Codes. IRENA 2016
2 Scaling up Variable Renewable Power: The Role of Grid Codes. IRENA 2016
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Table 1-1: Stability criteria according to ENTSO – Levels according to Consultant
Technologies Sho
rt C
ircu
it
Po
we
r Q
ual
ity
Bla
ck S
tart
Day
Nig
ht
Ine
rtia
Flu
ctu
atio
ns
Isla
nd
cap
abil
ity
Vo
ltag
e a
nd
fre
qu
en
cy r
egu
lati
on
PV
CSP (no storage)
CSP (with storage)
Wind (synchron machine)
Wind (DG asynchron machine)
Stabi l i ty cri teria (from ENTSO) - only i l lustrative - fina l result can be obtained only after network ca lculations
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2. Grid Connection Alternatives
This assignment focuses on grid connected solar and wind facilities and therefore it is of foremost im-
portance to locate these facilities at suitable distances from potential connection points. Typically suit-
able connection points are substations on the 66 or 30 kV level and under certain conditions at 220 kV
level for the case of Libya. A reasonable proximity to the connection points will not only reduce trans-
mission losses but will also maintain CAPEX at predictable levels as transmission lines are capital in-
tensive and require complex permits and authorization processes.
As indicated in section 1, this assignment, and for extension this section, does not deal with analyses
of power networks. Due to its complexity, such analyses if required shall be part of a separate as-
signment or shall be carried out during the implementation of the LCEP. It is a main assumption that
potential connection points/substations shall be analysed in more detail in further steps of implementa-
tion where decisions on either expansions or upgrades of these connection points shall be taken.
For the LCEP the Consultant will focus on existing substations by identifying connection points:
Either existing or planned, defined in the transmission system network studies;
Mentioned in existing feasibility studies;
Close to sites with existing ground measurements; and
Suggested by the stakeholders.
Figure 2-1 depicts a screenshot of the georeferenced Libyan grid as provided by GECOL to the Con-
sultant.
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Libya SPREL – LCEP Report – Annex II – Grid Connection Aspects
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Figure 2-1: Georeferenced Libyan grid as provided by GECOL3
The substations identified have been, to the extent possible, georeferenced, characterized and cross-
checked with the latest information provided by GECOL and the existing feasibility studies. The areas
proposed for the LCEP were presented and agreed with the stakeholders with no major objections to
use the substations on those areas for further analyses. A deeper analysis of the grid connection is a
task to be performed within the scope of a specific study for a specific plant.
With regard to the location of potential RE power plants, GECOL generally stated that such power
plants should be installed preferably more in the south of the overall transmission and distribution grid
(e.g. in the southern centres of the two main North-south branches of the grid). Since the main con-
ventional power plant fleet is located more in the northern coastal line, GECOL suggestion will help to
balance the overall load flow, to avoid negative impact of short circuit issues and overall stabilize with
this the system.
2.1 Transmission System Network Studies
In an initial step, the Consultant has screened the existing transmission system network studies for po-
tential substations near the representative sites defined for the LCEP analysis. Figure 2-2 sets out the
location of the identified substations and Table 2-1 summarizes the current status of the following in-
formation of each substation:
Name of substation in English language;
Voltage level;
Coordinates;
Available capacity of connection (MW); 3 Libyan networks georeferenced in GoogleEarth (.kmz file with substations), provided by GECOL, 2017
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Existing, under construction or planned; and
Year of installation.
This information allows the Consultant to determine the areas for installation with better resolution, as
well as the size of RE facilities and the distance of interconnection.
Figure 2-2: Potential connection points for RE facilities in Libya acc. to transmission studies
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Table 2-1: Summary of identified connection points – Transmission system network studies
Connection point - Substation
Name Coordinates Check with GECOL
geodata
Distance TFR Rating Capacity Year Voltage Planned load [MW] Av.
(Latitude, longitude) Name (Latitude, longitude) Info [km] [MVA] MW [kV] 2020 2025 2030 MW
Gyrian (MISSING) الهيره 32°27'3.87"N; 13° 2'9.07"E محطة تحويل 220/66/30/11 ك.ف الهيره 0 0
El Hira (MISSING) ابوعرقوب 32°25'15.03"N; 13°14'18.85"E محطة تحويل 220/30/11 ابوعرقوب 0 0
Alzahara (Azahra) 32°40'45.10"N; 12°52'44.50"E الزهراء 32°40'46.86"N; 12°52'43.32"E محطة تحويل 220 ك.ف الزهراء 40 126 101 1974 220/66/30 126 145 165 -64
Bir Huisa 32°31'26.30"N; 12°40'57.70"E PLANNED? 40 200 160 2015 220/30 26 30 34 126
Bir Alganam 32°21'6.00"N; 32°21'6.00"N بئر الغنم 32°21'3.19"N; 12°39'21.39"E محطة تحويل 220/30/11 ك.ف بئر الغنم 36 126 101 1981 220/30 144 165 188 -87
Mislata 32°35'28.68"N; 14° 4'14.93"E القره بولي 32°42'55.01"N; 13°47'9.22"E محطة 220/30/11 ك.ف القره بولي 20 200 160 2015 220/30 63 73 83 77
Wadi Rabea (Ramil?) 32°31'51.50"N; 13°56'12.71"E PLANNED? 11 200 160 2015 220/30 97 112 127 33
Tarhona 32°23'52.90"N; 13°38'17.20"E ترهونة 32°23'50.61"N; 13°38'15.89"E محطة تحويل 220/30/11 ك.ف ترهونة 31 63 50 1980 220/30 146 169 192 -142
Zlitan 32°27'13.31"N; 14°34'55.33"E حكمون 32°26'14.80"N; 14°33'28.29"E محطة تحويل 220/30/11 ك.ف حكمون زليتن 21 126 101 1980 220/30 107 123 140 -39
Misurata South 32°14'16.97"N; 14°56'43.25"E طمينه 32°14'59.64"N; 15° 7'27.03"E محطة تحويل 220/30/11 ك.ف طمينة 25 126 101 1983 220/30 22 25 28 73
Misurata Switching 32° 8'29.91"N; 15° 7'1.00"E PLANNED? 42 300 240 2015 220/30 116 134 153 87
Misurata Power (Steel 400?) 32°18'16.71"N; 15°11'22.56" مصراته المزدوجه 32°19'48.09"N; 15°14'37.70"E محطة 400/220/30 ك.ف مصراته المزدوجة 630 504 1988 220/30 650 650 650 -146
Misurata Power (Steel 400?) 32°18'16.71"N; 15°11'22.56" 32°19'50.65"N; 15°13'54.40"E محطة تحويل 220 ك.ف الحديد 750 E 400/220
Tripoli West 220/30 32°49'24.00"N; 12°58'24.00"E PLANNED? 126 101 1980 220/30 106 123 140 -39
Tripoli West 400/220 32°49'24.00"N; 12°58'24.00"E غرب طرابلس 32°49'22.81"N; 12°58'28.44"E محطة تحويل 400/220 ك.ف غرب طرابلس 1400 U 400/220
Homs Power 32°31'25.73"N; 14°20'47.73"E كعام 32°29'49.49"N; 14°25'9.10"E محطة تحويل 220/30/11 ك.ف كعام 126 101 1974 220/30 85 98 112 -11
Homs Power 32°31'25.73"N; 14°20'47.73"E ?? 1400 P 400/220
Zawia Power 32°47'15.20"N; 12°40'30.20"E 32°47'15.18"N; 12°40'27.64"E محطة تحويل 220/30/11 ك.ف الزاوية 300 240 2006 400/220 55 62 71 169
Zawia Power 32°47'15.20"N; 12°40'30.20"E 32°47'17.27"N; 12°40'16.71"E محطة تحويل 400/220 ك.ف الزاوية 450 E 400/220
Milita 32°50'46.90"N; 12°15'16.75"E [empty lot?] 32°50'51.28"N; 12°13'44.07"E محطة 220 ك.ف مجمع مليته المقترحة 200 160 2015 220/30 63 73 83 77
Milita 32°50'46.90"N; 12°15'16.75"E الجميل 32°52'32.48"N; 12° 4'25.03"E محطة تحويل 220/30/11 ك.ف الجميل 1640 P 400/220
Abu Kamash 32° 1'34.10"N; 11°47'44.70"E شكشوك 32° 2'6.12"N; 11°57'52.38"E محطة تحويل 220/66/11 ك.ف شكشوك 126 101 1980 220/30 39 45 51 50
Abu Kamash 32° 1'34.10"N; 11°47'44.70"E شكشوك 32° 2'6.12"N; 11°57'52.38"E محطة تحويل 220/66/11 ك.ف شكشوك 820 P 400/220
Bengazhi North Old 32°11'13.70"N; 20° 8'59.10"E شمال بنغازي 32°11'10.45"N; 20° 8'53.15"E محطة 220/30/11 ك.ف شمال بنغازي القديمة 83 66 1976 220/30 117 135 154 -88
Bengazhi North New+power 32°11'57.37"N; 20° 8'6.24"E شمال بنغازي 32°12'2.54"N; 20° 8'2.99"E محطة تحويل 400/220 ك.ف شمال بنغازي 126 101 2005 220/30 115 132 150 -49
Bengazhi North New+power 32°11'57.37"N; 20° 8'6.24"E شمال بنغازي 32°12'6.14"N; 20° 8'8.47"E محطة تحويل 220/30/11 ك.ف شمال بنغازي 820 E 400/220
Bengazhi West (See Gwarsha old - CLOSE) جنوب بنغازي 32° 1'50.33"N; 20° 6'52.54"E محطة تحويل 220/30/11 ك.ف جنوب بنغازي 1400 P 400/220
Gwarsha old 32° 0'0.80"N; 20° 4'23.10"E جنوب بنغازي 32° 1'50.33"N; 20° 6'52.54"E محطة تحويل 220/30/11 ك.ف جنوب بنغازي 315 252 1984 220/66/30 291 295 381 -129
Derna 32°46'23.49"N; 22°34'31.02"E 32°36'17.65"N; 22°46'9.07"E محطة تحويل /66/11 ك.ف الفتائح 126 101 1976 220/30 97 112 127 -26
Derna Al-Meyna 32°45'32.18"N; 22°39'17.19"E درنه 32°46'49.81"N; 22°35'12.16"E محطة تحويل 220/30/11 ك.ف درنة التوليد 300 240 2015 220/30 88 100 114 126
Al Fatiyah (MISSING) PLANNED? 200 160 2015 220/30 49 56 64 96
Tamimi 32°20'0.75"N; 23° 3'19.88"E التميمي 32°26'56.32"N; 23° 3'39.18"E محطة 220/66/11 ك.ف التميمي 15 126 101 1984 220/66 31 36 41 60
Beada North 32°47'9.02"N; 21°45'4.01"E البيضاء 32°46'41.08"N; 21°45'35.91"E محطة 220/30/11 ك.ف البيضاء 13 250 200 2009 220/66 85 98 111 89
Sebha Airport 26°57'47.70"N; 14°26'21.20"E سبها كم 18 26°53'11.66"N; 14°25'8.97"E محطة تحويل 220/66/11 ك.ف سبها كم 20 126 101 2015 220/66 24 29 33 68
Sebha North 27° 2'42.60"N; 14°26'31.70"E سبها 400 27° 2'23.98"N; 14°31'48.57"E محطة تحويل 400/220/66/11 ك.ف سبها 30 250 200 2010 220/66 158 163 150 50
Sebha North 27° 2'42.60"N; 14°26'31.70"E سبها الشمالية 27° 2'43.03"N; 14°26'35.38"E محطة تحويل 220 ك.ف سبها الشمالية
Sebha North 27° 2'42.60"N; 14°26'31.70"E سبها الغربية 27° 2'28.88"N; 14°23'51.91"E محطة تحويل 220 ك.ف سبها الغربية
Ghadamis 30°10'4.80"N; 9°45'21.60"E غدامس 30° 8'57.23"N; 9°29'26.49"E محطة تحويل 400/220 ك.ف غدامس 6 0 440/220/66 21 25 28 -28
Ghadamis 30°10'4.80"N; 9°45'21.60"E 30°10'13.76"N; 10° 0'40.78"E محطة كهرباء
Brega 30°26'6.10"N; 19°42'25.30"E اجدابيا 30°55'24.60"N; 20°11'26.54"E محطة تحويل 400/220 ك.ف اجدابيا 53 126 101 1984 220/30 93 106 121 -20
Ras Lanof 30°34'26.15"N; 18°25'6.34"E راس النوف 30°27'48.85"N; 18°32'46.92"E محطة 400/220/66 ك.ف راس النوف 90 126 101 2006 220/66/306 63 73 83 18
Hoon 29° 8'50.18"N; 16° 0'59.66"E هون 29° 7'2.26"N; 15°53'28.96"E محطة تحويل 220/66/11 ك.ف هون 1,5 189 151 1983 400/220/66 111 128 146 5
Thala 25°47'16.76"N; 10°33'18.82"E العوينات 25°47'16.76"N; 10°33'18.82"E محطة 220/66/11 ك.ف العوينات
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2.2 Connection Points for Sites Suggested by Stakeholders
Further to those sites where measurement campaigns have been carried out, GECOL and REAOL
suggested other sites for which the connection points (substations) have been preliminarily identified.
Table 2-2 shows for the sites suggested by the stakeholders the connection points identified by the
Consultant.
Table 2-2: Substations identified for sites suggested by stakeholders
Substations
Area City/town Coordinates (Latitude, longitude)
SS Name (arabic)
SS Name (english)
Coordinates (Latitude, longitude)
Distance (km)
Tripoli Zliten 32°12'37"N; 14°30'1"E البرج Zliten SS 32°12'38.00"N; 14°34'51.00"E 5
Bengazhi Al Tamimi 32°27'2"N; 23° 5'28"E التميمي Tamimi 32°26'56.32"N; 23° 3'39.18"E 3
Brega Brega 30°23'37"N; 18°41'56"E راس النوف Raz Lanof 30°27'48.85"N; 18°32'46.92"E 16
Jagboub Jagboub 29°44'28"N; 24°30'0"E Aljagboub 29°44'45.00"N; 21°17'58.00"E 300
Jagboub Kufra1 27°38'53"N; 21°42'47"E 52.58'35°27 السرير"N; 21°36'48.66"E 7
Jagboub Kufra2 26°56'49"N; 22° 9'3"E السرير
الجنوبي 26°54'33.47"N; 22° 5'53.83"E 10
2.3 Conclusions on Grid Connection Alternatives
The set of grid connection alternatives so far identified allows the Consultant to overlap the potential
sites with the topology of the Libyan power network in order to better define the potential development
of RE within the term of analysis of the LCEP i.e. until 2030.
Libya - Supporting Electricity Sector Reform (P154606)
Contract No. 7181909 - Task D: Strategic Plan for Renewable Energy Development
Least Cost Expansion Plan Report Annex III –Potential Areas and Sites 12 December 2017
Client:
The World Bank
1818 H Street, N.W.
Washington, DC 20433
Consultant:
GOPA-International Energy Consultants GmbH
Justus-von-Liebig-Str. 1, 61352 Bad Homburg, Germany
Phone: +49-6172-1791-800; Fax: +49-6172-944 95 20
eMail: info@gopa-intec.de; www.gopa-intec.de
Suntrace GmbH
Grosse Elbstrasse 145c, 22767 Hamburg, Germany
Phone: +49-40-767 96 38 0; Fax: +49-40-767 96 38 20
www.suntrace.de
Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites
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Table of Contents Page
1. Site restrictions 3
1.1 Environmental Restrictions 3
1.2 Adverse Climatic Conditions 3
1.3 Accessibility 4
1.4 Allocated Areas for Oil Field Exploitation or Exploration 4
1.5 Security and Integrity of Facilities 4
2. Environmental Aspects in Libya 5
3. Identification of Potential Areas and Sites 8
3.1 Areas for the LCEP 8
3.1.1 Tripoli Area 9
3.1.2 Bengazhi Area 10
3.1.3 Sebah Area 11
3.1.4 Ghadamis, Brega and Hun Areas 12
3.1.5 Thala and Jagboub Areas 14
3.2 Final Representative Sites for the LCEP 16
List of Tables
Table 1-1: Some of the national parks and nature reserves in Libya
Table 3-1: Final set of sites and technology configurations for the LCEP
List of Figures
Figure 3-1: Preselected areas for the LCEP
Figure 3-2: Conventions used in the maps
Figure 3-3: Tripoli area (Google Earth)
Figure 3-4: Bengazhi area (Google Earth)
Figure 3-5: Sebah area (Google Earth)
Figure 3-6: Ghadamis area (Google Earth)
Figure 3-7: Brega area (Google Earth)
Figure 3-8: Hun area (Google Earth)
Figure 3-9: Thala area (Google Earth)
Figure 3-10: Jagboub area (Google Earth)
Figure 3-11: Location of selected RE plants for LCEP
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Abbreviations CAPEX Capital Expenditures
CCGT Combined Cycle Gas Turbine
CRS/CR Central Receiver System
CSP Concentrating Solar Power
DNI Direct Normal Irradiation
DSG Direct Steam Generation
ENTSO European Network of Transmission System Operators
ESS Energy Storage System
FLH Full Load Hours
GECOL General Electric Company of Libya
GHI Global Horizontal Irradiation
GI Global Irradiation
GT Gas Turbine
HFO Heavy Fuel Oil
HRSG Heat Recovery Steam Generator
HTF Heat Transfer Fluid
IDC Interest During Construction
IEC International Electro-chemical Commission
IGBT Insulated Gate Bipolar Transistor
IPP Independent Power Producer
IRR Internal Rate of Return
ISCC Integrated Solar Combined Cycle
ITRPV International Technology Roadmap for Photovoltaic
LCEP Least Cost Expansion Plan
LCoE Levelized Cost of Electricity
LDS Long-Duration Energy Storage
LFO Light Fuel Oil
LID Light Induced Degradation
LLJ Low Level Jet
LVRT Low Voltage Ride Through
OPEX Operational Expenditures
PID Potential Induced Degradation
PPA Power Purchase Agreement
PSP Private Sector Participation
PT Parabolic Trough
PV Photovoltaics
RE Renewable Energies
REAOL Renewable Energy Authority of Libya
SCA Solar Collector Arrangement
SCGT Simple Cycle Gas Turbine
SM Solar Multiple
STATCOM Static Compensators
SPREL Strategic Plan for Renewable Energies in Libya
TES Thermal Energy Storage
TMY Typical Meteorological Year
TSC Thyristor Switched Capacitors
WACC Weighted Average Capital Cost
WB World Bank
WTG Wind Turbine Generator
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1. Site restrictions
The overview on site restrictions in Libya will enable the Consultant to identify those areas which are
restricted to installation of RE generation facilities. Based on the information collected the Consultant
will focus on environmental restrictions, exclusion areas for oil and gas exploration / exploitation, re-
stricted accessibility for construction, adverse climatic conditions and security restrictions, as de-
scribed below.
1.1 Environmental Restrictions
National parks and nature reserves can be considered as restricted areas due to environmental and
conservation reasons. Table 1-1 lists the national parks and nature reserves in Libya1. These areas
will be excluded for a selection of potential sites for RE implementation.
Table 1-1: Some of the national parks and nature reserves in Libya
Protected area Date of creation Total area (Ha) Status
El Kouf 1978 100,000 National Park
Alhesha 1984 160,000 Nature reserve
Algharabolli 1992 8,000 National Park
Abughylan 1992 4,000 National Park
Bir Ayad 1992 12,000 Nature reserve
Surman 1992 4,000 National Park
El Naggaza 1993 4,000 National Park
Sabrata 1995 500 National Park
Msalata 1998 1,800 Nature reserve
Nalout 1998 200 Nature reserve
Zulton 1998 1,000 Nature reserve
1.2 Adverse Climatic Conditions
Adverse climatic conditions such extreme high temperatures and sand storms will affect negatively the
implementation of RE. Although irradiance might be higher in areas with higher temperatures, some-
times it is not worth the trade off as technologies might be affected by high temperatures and dust with
the subsequent curtailment of electricity production. As an example normal WTGs usually will be
stopped when temperatures exceed some 45°C.
The highest values of DNI irradiance can be found for the Tibesti Massif in the South. However, this
region is very hard accessible and an almost total empty desert countryside, thus no option for solar
energy.
1 Bouras, Essam M. "National parks and reserves" (PDF). Head, of protected area & biodiversity section, Nature conservation
Dept, Environment General Authority, Convention on Biological Diversity. Retrieved 26 March 2013
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The south area, the Sahara desert, is also well known for their adverse climatic conditions and little
settlements and grid connection possibilities exist, thus this area will not be the focus for potential im-
plementation of RE.
1.3 Accessibility
Areas not accessible for transportation of large equipment will not be considered for further analyses.
Although this is more relevant for CSP and WTGs the Consultant will initially exclude those areas for
further analyses for all technologies and focus on areas with suitable access.
1.4 Allocated Areas for Oil Field Exploitation or Exploration
The Consultant assumes that oil field areas cannot be considered for RE implementation. Further, the
Consultant tried to the extent possible to identify the boundaries of those areas as well as other areas
allocated for oil and gas exploration.
1.5 Security and Integrity of Facilities
Due to the ongoing conflict it is necessary to identify together with other stakeholders the areas and
technologies which are preferred for deployment of RE during the implementation of the LCEP.
Amongst others, issues related to safe access to construction sites and sabotage/destruction of elec-
tricity generation facilities were discussed with the stakeholders.
It is important to highlight that WTGs and solar towers are an easier infrastructure target for sabotage
or destruction if this is the case. In addition, CSP due to its nature of one single generator pose more
risk of shortfall if damaged than wind and PV which are inherently scalable.
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2. Environmental Aspects in Libya
The following laws form the regulatory framework for environmental impacts assessment in Libya, with
focus on renewable energy projects.
The Law No. 15 of 20032 on protection and improvement of the environment is the main EIA relat-
ed legislative framework in Libya. The law has 12 chapters and 79 articles. The law stipulates re-
sponsibilities of the public authorities and the projects proponents towards preserving the environ-
ment in the following fields:
– General Provision (Articles 1 – 9);
– Air Pollution (Articles 10 – 17);
– Protection of Sea and Marine wealth (Articles 18 – 38);
– Protection of Water Sources (Articles 39 – 47);
– Protection of Foodstuffs (Articles 48 – 50);
– Environmental Hygiene (Article 51);
– Protection from Common Animal Diseases (Article 52);
– Protection of Soil and Plants (Article 53 – 55);
– Protection of Wildlife (Article 56 – 57);
– Biological Safety (Article 58 – 63);
– Penalties (Articles 64 – 76); and,
– Final Provisions (Articles 77 – 79).
National Oil Corporation's Environmental Impact Assessment Guidelines
The National Oil Corporation's Environmental Protection Department's "Environmental Impact As-
sessment Guidelines for Seismic Operations" was published in 2006 and constitute the guidelines for
conducting environmental impact assessments in Libya. The guide defines the following steps as be-
ing required:
– Scoping: defining the geographical area to be surveyed, ecosystems, land-use and an indica-
tion of the area likely to be affected;
– Assessment: identification of potential impacts, anticipation of their scale, duration and severity
followed by recommendation of mitigation measures presented within an Environmental Man-
agement Plan;
– Key stakeholders consultation: usually discussions with the NOC and department of antiquities;
and,
– Follow up: ensuring that mitigation measures are being implemented, usually through inde-
pendent audits and monitoring.
On the other hand, The National Oil Corporation's has also set HSE guidelines. The National Oil Cor-
poration acts as ministry, regulatory agency, and state-owned company3.
Law No. 426 establishing the Renewable Energy Authority of Libya4
2Law 15 (1371) ; 2003 on protection and improvement of environment
3http://www.resourcegovernance.org/our-work/country/libya
4http://www.iea.org/policiesandmeasures/pams/libya/name-24772-en.php
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The Libyan government created the Renewable Energy Authority of Libya (REAOL) in 2007. The main
goal of the REAOL is to implement proper policies so as to meet the governmental target of a 10%
share of the total energy mix coming from renewable energy sources by 2020. The REAOL imple-
ments renewable energies projects, encourages and supports related industries, proposes supporting
legislation and regulations and evaluates Libyan renewable energy potentials to identify priority areas.
REAOL also has the mandate to assess in developing regulatory and industry infrastructure, and as-
sess and conducting renewables resources mapping.
Other relevant laws are
– Law No (5) of 1969 on the organization and planning of towns and villages amended by law No.
(3) of 2002;
– Law No (38/39) of 1975, concerning municipalities organizing actions, defining in details con-
cerned with environmental protection;
– Law on the Protection of Agricultural Lands (No. 33 of 1970);
– Law on Range and Forest Protection (No. 5 of 1982);
– Decision no (81) for 1976: Model regulation to Regulate the Water and Drainage Utility at the
Municipalities (28 April 1976);
– Decision no (94) for 1976: Model Regulation Related to Public Cleanliness (16 May 1976);
– Decision no (142) for 1976: Rules for Disposal of Waste Materials at the Municipalities (19 May
1976);
– Law on Water Use (Law No. 3 of 1982);
– Law on Protecting Animals and Trees (No. 15 of 1989);
– Health Law No. 106 (1973) – Details aspects of environmental protection including water pollu-
tion and sampling;
– Labour Law (No. 58 of 1970);
– General Peoples Council Decision No. 8 of 1974 – Protection and Security of Employees; and
– Law on Industrial Security and Labour Safety (No. 93 of 1976).
International conventions signed by Libya
– Convention on Preservation of Fauna and Flora in their Natural State (London , 1933);
– African Convention on the Conservation of Nature and Natural Resources (Algeria , 1968 );
– Convention on Wetlands (Ramsar, 1971);
– World Heritage Convention (Paris, 1972);
– Convention on International Trade in Endangered Species of Fauna and Flora (CITES Wash-
ington, 1973);
– Convention for the Protection of the Mediterranean Sea against Pollution (Barcelona, 1976);
– Convention on the Conservation of Migratory Species of Wild Animals (Bonn, 1979);
– United Nations Convention on the Law of the Sea (UNCLOS) (Montegoby, 1982);
– The Basel Convention on the Transboundary Movement of Hazardous Wastes and their Dis-
posal (Basel, 1989);
– Bamako Convention on the Ban of the Import Into Africa and the Control of Transboundary
Movement and Management of Hazardous Wastes Within Africa (Mali,1991);
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– Convention on Biological Diversity (Rio, 1992);
– 16th November 1994. Libya has signed but not yet ratified the convention;
– Cartagena Protocol on Biosafety to the convention on biological diversity (Montreal , 2000);
– UN Framework Convention on Climate Change, Climate Change-Kyoto Protocol;
– United Nations Paris Agreement on climate change (not yet ratified);
– UN Convention on Combating Desertification; and
– Vienna Convention for the protection of the Ozone Layer.
Final notes on environmental aspects
Since, to the Consultant’s understanding and information received, Libya has no operational "large
scale renewable energy projects" it is assumed that experience in dealing with environmental issues
shall be learnt based on the experience of oil projects which usually have a strong impact on the envi-
ronment.
From a preliminary appraisal the Libyan environmental regulations are less restrictive than in the Eu-
ropean Union and thus for preliminary assessments as this ongoing technology assessment, critical
environmental restrictions will be identified in accordance with international environmental standards
as such in the European Union. The more relevant issues affecting CSP solar towers and WTGs
would be issues related to birds.
Environmental impacts shall always be ultimately dealt with for specific projects. Environmental as-
pects will be closer evaluated for the site selection and feasibility of the pilot PSP project in stage III of
this assignment.
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3. Identification of Potential Areas and Sites
For the purposes of the LCEP the Consultant has so far performed a desktop appraisal of the solar re-
source and potential connection points as they are the two most important aspects. Further to these
aspects, the Consultant has also preliminarily performed a desktop appraisal of:
Land required by different technology configurations;
Environmental restrictions;
Topography;
Proximity to demand centres or areas with important demand growth;
Water availability; and
Access and transportation infrastructure for especial equipment including roads and railways.
The objective is to screen the country for the most convenient areas for wind and/or solar implementa-
tion within the term of the LCEP and according to the information available. Thus these aspects were
not analysed in detail but only dealt with to the extent that allows the Consultant to identify whether
major constraints exist leading to exclude an area or a technology configuration from the LCEP pro-
cess. A detailed analysis can only be performed for specific projects.
3.1 Areas for the LCEP
Based on the analyses performed in Annex II and Annex III the Consultant has identified main areas
for installation of RE facilities as shown in Figure 3-3. This section presents an overview of these are-
as, as well as other assumptions made in order to evaluate and rank them for preparation of the
LCEP.
Figure 3-1: Preselected areas for the LCEP
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The following assumptions were made by the Consultant in order to define the areas proposed for the
LCEP:
Areas considered for the LCEP shall be large enough to reduce issues related to exclusion of are-
as due to environmental aspects (e.g. natural reserves) or land use (e.g. areas reserved for oil ac-
tivities);
Water availability will not be considered a major issue since CSP plants will be equipped with dry
cooling systems;
GECOL recommendation that RE facilities may be installed preferably more in the south of the
overall transmission and distribution grid (e.g. in the southern centres of the two main North-south
branches of the grid); and
A major need of present and future demand is expected close to Tripoli.
For the purposes of the LCEP the Consultant has selected areas for further analyses and ranking i.e.
Tripoli, Bengazhi, Sebah, Ghadamis, Brega, Hun; Thala and Jagboub. An overview of these areas is
presented in the sections below.
Figure 3-2 sets out the conventions used throughout this section in order to easily identify objects
herein.
Figure 3-2: Conventions used in the maps
3.1.1 Tripoli Area
Although no feasibility study for RE has been performed within this area, the Tripoli area is the major
consumer area in Libya also characterized for a good quantity of potential connection points and good
infrastructure for transport due to the proximity to the north coast. In terms of resource the area offers:
Spots with very good wind resource and wind ground measurements at Aziziya, Assaba, Misalatah,
Misurata, Gotteria and Tarhona. Although these measurements are not bankable (see Annex II)
they may help reduce the uncertainty for energy yield estimations; and
Reduced solar irradiation in comparison with other areas in Libya with solar ground measurements
of GHI and DNI at Bir Al-Gahnam.
Identified potential sites for:
Wind are: Assaba, Aziziya, Misalata and Misurata; and
Solar are: Jadu for PV and CSP and Zliten only for PV.
Security is not a high concern in this area according to the Consultant’s information.
A preliminary snap shot of the Tripoli area is shown in Figure 3-3.
SubstationWind mastPV/CSP Plants
Area for REGenerator 400 kV 220 kV 66 kV132 kV
PV PlantsWind Farm Solar met station
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Figure 3-3: Tripoli area (Google Earth)
3.1.2 Bengazhi Area
The Bengazhi area is located in the north-west part of the country in the proximities of the city of Ben-
gazhi. Different to the Tripoli area, this area includes sites some hundred kilometres away from Ben-
gazhi, the main consumption center, to the west such as Tamimi, Dernah, Al Maqron and Shahat.
Although solar resource in this area is not the highest in Libya it is still very good resource for both PV
and CSP deployments. Wind resource is very attractive in this area, chiefly in the plateau some kilo-
metres to the south of the coastal line.
Feasibility studies have been performed already in this area for wind, PV and CSP being the Dernah
wind park development the most advanced of them all achieving delivery of components of the WTGs
to the area. The Dernah wind project was put on hold due to security reasons in the area and accord-
ing to recent information, its location is being modified. Although Dernah is still undergoing security is-
sues these could be transitory and thus this situation will not negatively affect the location for the
LCEP.
It is important to clarify the status of interconnection between east and west of Libya since according
to information received the transmission line could be disconnected due to serious damages of infra-
structure near Bengazhi. This area is also a main demand centre of the country although considerably
less demand is expected there in comparison to Tripoli area.
Figure 3-4 shows a snapshot of the Bengazhi area.
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Figure 3-4: Bengazhi area (Google Earth)
3.1.3 Sebah Area
The Sebah area is located approximately 650 km south of Tripoli and encompasses the area nearby
Sebah city, capital of the Sebah district. The area offers a very good solar resource and good wind re-
source, alongside with good transport infrastructure and security conditions. Feasibility studies for both
a PV and a CSP plants have been already performed in this area. GHI measurements have been tak-
en in this area at Sebah and Argiba, unfortunately the data of the former location are missing.
The site at Edri has been recommended by REAOL and GECOL since the area is available and al-
ready secured by the Libyan government for solar power developments. Wanzreck substation has
been confirmed by GECOL for connection of solar plants.
Another attractive aspect of this area is the vicinity to an important consumption centre of the country
and therefore the Consultant considers it as an integral area for the LCEP.
Figure 3-5 shows a snapshot of the Sebah area.
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Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites
LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx
Figure 3-5: Sebah area (Google Earth)
3.1.4 Ghadamis, Brega and Hun Areas
Ghadamis. Brega and Hun areas offer good wind and solar resources together with sufficient potential
for connecting RE facilities to the Libyan grid. Although not as important as the Tripoli, Bengazhi and
Sebha areas the Consultant recommends the implementation of RE in these areas as part of the
LCEP as they will help deploying solar and wind facilities close to remote consume centres. RE pro-
jects in these areas will support the stability of the network and reduce transmission losses while ben-
efiting from the infrastructure associated to the nearby settlements.
Figure 3-6, Figure 3-7 and Figure 3-8 show snapshots of the Ghadamis, Brega and Hun areas respec-
tively for reference.
Ghadamis and Hun areas have solar measurement systems for GHI with available data. There is also
available DNI data at Ghadamis.
Although there are no measurements in Brega the Consultant recommends this area for wind power
facilities due to the high wind resource and infrastructure in the area.
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Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites
LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx
Figure 3-6: Ghadamis area (Google Earth)
Figure 3-7: Brega area (Google Earth)
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Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites
LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx
Figure 3-8: Hun area (Google Earth)
3.1.5 Thala and Jagboub Areas
The Thala and Jagboub areas offer a good solar resource together with sufficient potential for con-
necting RE facilities to the Libyan grid. Different to the other areas these areas have been suggested
by GECOL as they are of essential importance for electricity supply as they are in very remote areas.
PV plants will be considered in these areas for the LCEP term since restrictions in accessibility and
harsh climatic conditions will make CSP and wind developments difficult. Such issues are to be ad-
dressed via a feasibility study for a concrete development.
For the Jagboub area, three sites have been considered for simulation of the PV plants i.e. Jagboub,
Kufra1 and Kufra2. There is no ground data available for the Jagboub area. The intention of these
sites is to analyse how they will be incorporated in the LCEP mix.
The Thala area has GHI ground measurement at Ghat site and a substation for connection of solar
power at the Thala substation.
Figure 3-9 and Figure 3-10 show snapshots of the Thala and Jagboub areas for reference.
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Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites
LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx
Figure 3-9: Thala area (Google Earth)
Figure 3-10: Jagboub area (Google Earth)
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Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites
LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx
3.2 Final Representative Sites for the LCEP
The process and criteria applied so far allowed the Consultant to identify a set of sites and technology
configuration representative for Libya which will be the base to perform the simulations and prepare
the economic indicators for optimization of the LCEP mix of RE.
The set of representative sites and technology configurations, including substations, met stations and
short-term restrictions is shown in Table 3-1. Figure 3-11 shows the final proposed RE plants for the
LCEP.
It is also important to note that distances to substations were roughly estimated in order to add
CAPEX for connection. Whereas some sites are suitable for the PV, CSP and wind others are pro-
posed for only one or two technologies. Larger areas were checked for CSP due to the storage capa-
bility and hence the larger solar field.
Figure 3-11: Location of selected RE plants for LCEP
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Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites
LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx
Table 3-1: Final set of sites and technology configurations for the LCEP
Meteorological station Substations Voltage Technology Configurations
Area City/town Coordinates
(Latitude, longitude)
Min. Max. Name Coordinates
(Latitude, longitude)
Distance
(km)
SS Name
(arabic)
SS Name
(english)
Coordinates
(Latitude, longitude)
Distance
(km)
[kV] PV CSP WIND BATTERY
Tripoli Aziziya 32°19'52"N; 13° 3'7"E 200 Aziziya 32°19'51.82"N; 13° 3'6.70"E 0 الهيره El Hira 32°27'3.87"N; 13° 2'9.07"E 13 220/66/30/11 WIND1;WIND2
Tripoli Misallatha 32°38'59"N; 13°53'27"E 400 Misallatha 32°36'41.20"N; 13°51'34.25"E 0 القره بولي 32°42'55.01"N; 13°47'9.22"E 12 220/30/11 WIND1;WIND2
Tripoli Misurata 32°28'7"N; 14°48'47"E 200 Misurata 32° 6'11.53"N; 15°10'26.43"E 60 حكمون 32°26'14.80"N; 14°33'28.29"E 11 220/30/11 WIND1;WIND2
Tripoli Assaba 32° 7'20"N; 12°52'40"E 50 200 Assaba 32° 7'19.67"N; 12°52'39.94"E 0 الرابطه 32°13'7.61"N; 12°53'54.82"E 10 220/30/11 WIND1;WIND2
Tripoli Zliten 32°12'37"N; 14°30'1"E 50 200 satellite data البرج Zliten SS 32°12'38.00"N; 14°34'51.00"E 5 30 PV1; PV2;PV3;PV4
Tripoli Jadu 32° 5'55"N; 12° 4'47"E 50 200 Bir al Gahnam 32° 21' 3.19" N; 12° 39' 21.39" E 60 شكشوك Shakshuk 32° 2'6.12"N; 11°57'52.38"E 13 220/66/11 PV1; PV2;PV3;PV4 CSP1;CSP2;CSP3;CSP4
Bengazhi Derna 32°42'37"N; 22°45'14"E 100 Derna 32°42'38.46"N; 22°45'13.99"E 0 محطة تحويل 32°36'17.65"N; 22°46'9.07"E 12 66/11 WIND1;WIND2
Bengazhi Al Maqron 31°15'48"N; 20°49'59"E 50 200 Al Maqron 31°15'48.55"N; 20°49'58.58"E 0 اجدابيا 31°27'2.50"N; 20° 9'30.90"E 64 400/220 WIND1;WIND2
Bengazhi Al Tamimi 32°27'2"N; 23° 5'28"E 100 100 satellite data التميمي Tamimi 32°26'56.32"N; 23° 3'39.18"E 3 220/66 CSP1;CSP2
Bengazhi Shahat 32°48'37"N; 21°44'16"E 50 Shahat 32°45'36.00"N; 21°53'24.00"E 15 البيضاء Beada 32°46'41.08"N; 21°45'35.91"E 4 220/66 PV1; PV2;PV3;PV4
Sebah Sebah 26°47'20"N; 14°25'16"E 100 50 Sebah 26°47'19.65"N; 14°25'16.22"E 4 سبها كم 18 Sebha 26°53'11.66"N; 14°25'8.97"E 13 220/66 PV1; PV2;PV3;PV5 CSP1;CSP2
Sebah Edri 27°29'19"N; 13°10'50"E 50 100 Argiba 26°34'50.28"N; 13°34'25.56"E 100 Wanzreck 27°29'20.60"N; 13°10'47.78"E 0.5 66/11 PV1; PV2;PV3;PV4
Ghadamis Ghadamis 30° 5'35"N; 9°36'17"E 50 50 Ghadamis 30°10'4.80"N; 9°45'21.60"E 17 غدامس Ghadamis 30° 8'57.23"N; 9°29'26.49"E 13 440/220 PV1; PV2;PV3;PV4
Brega Brega 30°23'37"N; 18°41'56"E 100 satellite data راس النوف Raz Lanof 30°27'48.85"N; 18°32'46.92"E 16 220/66/306 PV1; PV2;PV3;PV4 CSP1;CSP2
Hun Hun 29° 8'34"N; 15°51'34"E 50 100 Hun 29° 9'15.69"N; 16° 0'17.60"E 15 هون Hoon 29° 7'2.26"N; 15°53'28.96"E 4 220/66/11 PV1; PV2;PV3;PV4 CSP1;CSP2
Ghat Thala 25°24'37"N; 10°21'34"E 50 200 Ghat 24°57'51.53"N; 10°10'32.72"E 52 Thala 25°24'29.22"N; 10°21'25.88"E 0.5 400/220/66 PV1; PV2;PV3;PV4
Jagboub Jagboub 29°44'28"N; 24°30'0"E 50 100 satellite data Aljagboub 29°44'45.00"N; 21°17'58.00"E 300 66 PV1; PV2;PV3;PV4
Jagboub Kufra1 27°38'53"N; 21°42'47"E 50 100 satellite data السرير 27°35'52.58"N; 21°36'48.66"E 7 220/66/11 PV1; PV2;PV3;PV4
Jagboub Kufra2 26°56'49"N; 22° 9'3"E 50 100 satellite data السرير الجنوبي 26°54'33.47"N; 22° 5'53.83"E 10 220 PV1; PV2;PV3;PV4
750 2750 Technology configurations
PV1 - 50 MWac; Fix
mounted; p-Si modules;
central inverter
CSP1 - 100 MW gross PTC with
thermal oil as HTF; Air Cooled
Condenser; Molten salt two
tanks of 7 FLH and SM 3
WIND1 - 50 MW wind park; 2
MW turbines, 90 m hub height,
90 m diameter
BTT1 - Li-IonBattery storage of
10 MW and 7 hours
PV2 - 100 MWac; Fix
mounted; p-Si modules;
central inverter
CSP2 - 100 MW CRS with
molten salt as HTF; Air Cooled
Condenser; Molten salt two
tanks of 10 FLH and SM 3
WIND2 - 100 MW wind park; 3.5
MW turbines; 110/120 m hub
height; approx. 120 m diameter
PV3 - 50 MWac; 1-axis
tracked; p-Si modules;
central inverter
CSP3 - 100 MW PTC with
thermal oil as HTF; Air Cooled
Condenser; Molten salt two
tanks of similar TES capacity of
13 FLH and SM of 4
PV4 - 100 MWac; 1-axis
tracked; p-Si modules;
central inverter
CSP4 - 100 MW CRS with
molten salt as HTF; Air Cooled
Condenser; Molten salt two
tanks of 15 FLH and SM of 4
BTT1
Capacity [MW]
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Libya SPREL – LCEP Report – Annex III – Potential Areas and Sites
LBY2560_TaskD_ StageI_LCEP_Report_AnnexIII_PotentialAreas.docx
Libya - Supporting Electricity Sector Reform (P154606)
Contract No. 7181909 - Task D: Strategic Plan for Renewable Energy Development
Least Cost Expansion Plan Report Annex IV – Information Collected 12th December 2017
Client:
The World Bank
1818 H Street, N.W.
Washington, DC 20433
Consultant:
GOPA-International Energy Consultants GmbH
Justus-von-Liebig-Str. 1, 61352 Bad Homburg, Germany
Phone: +49-6172-1791-800; Fax: +49-6172-944 95 20
eMail: info@gopa-intec.de; www.gopa-intec.de
Suntrace GmbH
Grosse Elbstrasse 145c, 22767 Hamburg, Germany
Phone: +49-40-767 96 38 0; Fax: +49-40-767 96 38 20
www.suntrace.de
- 1 -
Table of Contents Page
1. Existing Studies and Information Collected 2
- 2 -
1. Existing Studies and Information Collected
In order to identify these connection points and determine the inputs for the LCEP, GECOL and
REAOL have provided the Consultant with the following information:
Consultancy for updating the transmission network expansion studies 2010 - 2030, 2020 - 2025 -
2030 Power System Studies Final Report, October 2010;
Feasibility Study Hun - 14MW PV Plant, REAoL & GIZ, Dr. Christian Bornhauser, Jan 2014;
Feasibility Study Sabha 40 MW PV, REAoL & GIZ, August 2013 (PRESENTATION);
Project Information Memorandum for a 5 and 10 MW PV Plants, EMPower Program Phase II, Lib-
ya, June2010;
Different sets of solar and wind ground measurement data;
Wind resource analysis, Tender Dernah wind farm, mTorres, Wind energy division, October 2010;
Preliminary Environmental Assessment, Wind farm, City of Derna, ELARD for REAoL, Feb. 2014;
Preliminary Environmental Assessment, Solar PV Plant in the City of Hun, ELARD for REAoL, Feb.
2014;
Analysis of Wind Energy Conversion Systems in Two Selected Sites in Libya Using Levelized Cost
of Electricity (LCOE), Paper of the University of Tripoli, 2016;
Renewable Energy and Energy Efficiency in Libya - Situation - Challenges and Prospects, REAoL,
January 2015 (PRESENTATION);
Feasibility Study for a Solar Thermal Power Plant in Libya, 100 MW Booster Heater, Abengoa So-
lar, October 2009 (CONFIDENTIAL);
Project Information Memorandum for a 50 MW CSP Plant, EMPower Program Phase II, Libya,
June2010;
Google Earth georeferenced grid data including the complete network, generators and substations
(My Places on google2017.kmz);
“تاج مخطط xlsx” provided by GECOL on 27.2017-3-5 اإلنth March 2017;
MENA CSP KIP, in-depth technical assistance in Jordan (ITA Inception note MA 050317.docx);
PWC, Rapid assessment of the sector performance, World Bank, April 2017;
List and data of substations in the Libyan grid (partial);
Libyan networks georeferenced in GoogleEarth (.kmz file with substations);
PWC, Simplified gas consumption estimate, World Bank, May 2017; and
Daily generation reports of 2016, GECOL.
Libya - Supporting Electricity Sector Reform (P154606)
Contract No. 7181909 - Task D: Strategic Plan for Renewable Energy Development
Least Cost Expansion Plan (LCEP) Annex V – Projected Performance of Conventional Plants 12th December 2017
Client:
The World Bank
1818 H Street, N.W.
Washington, DC 20433
Consultant:
GOPA-International Energy Consultants GmbH
Justus-von-Liebig-Str. 1, 61352 Bad Homburg, Germany
Phone: +49-6172-1791-800; Fax: +49-6172-944 95 20
eMail: info@gopa-intec.de; www.gopa-intec.de
Suntrace GmbH
Grosse Elbstrasse 145c, 22767 Hamburg, Germany
Phone: +49-40-767 96 38 0; Fax: +49-40-767 96 38 20
www.suntrace.de
- 2 -
Table of Contents Page
1. TASK A’s Technical Availability and Thermal Efficiency of Conventional Power Plants 3
- 3 -
1. TASK A’s Technical Availability and Ther-mal Efficiency of Conventional Power Plants
The following tables summarize the availability and thermal efficiency for worst and best case scenari-
os used by TASK A for the estimation of fuel consumption.
- 4 -
WORST case Technical availability
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Type of plant Power Station 8 7 10 11 14 16 15 16 17 16 16 15 15 15 15
Existing Various Small / rented 0% 4% 85% 85% 85% 85% 85% 85% 85% 85% 85% 85% 85% 85% 85%
Steam Khoms 91% 80% 80% 80% 80% 80% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Derna 1% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Tobruk 32% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Misurata Steel 0% 12% 71% 71% 71% 71% 71% 71% 71% 0% 0% 0% 0% 0% 0%
Gulf 44% 0% 43% 43% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%
Tripoli West 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Benghazi North 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Gas Tripoli South 90% 80% 82% 85% 85% 85% 85% 85% 85% 85% 88% 88% 88% 88% 88%
Zwetina 39% 33% 33% 74% 79% 79% 85% 85% 85% 85% 85% 85% 85% 85% 85%
Khoms 1 93% 82% 82% 87% 87% 87% 87% 87% 87% 87% 87% 0% 0% 0% 0%
Western Mountain 89% 72% 72% 83% 83% 83% 83% 83% 83% 83% 83% 83% 83% 83% 83%
Sarir 38% 22% 22% 22% 22% 53% 53% 53% 80% 80% 80% 80% 80% 80% 80%
Khoms 2 (Fast Track) 0% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95%
CC Zawia 80% 68% 68% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88%
Benghazi North 1 30% 38% 54% 59% 59% 59% 74% 88% 88% 88% 88% 88% 88% 88% 88%
Misurata 92% 45% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88%
Benghazi North 2 81% 69% 71% 85% 85% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88%
Under contr. Steam Gulf 0% 0% 0% 0% 0% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%
/ contracted Tripoli West 0% 0% 0% 0% 44% 58% 66% 96% 96% 96% 96% 96% 96% 96% 96%
Tripoli East 0% 0% 0% 0% 0% 88% 44% 88% 88% 88% 88% 88% 88% 88% 88%
Gas Ubari 0% 0% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80%
Misurata 0% 0% 0% 0% 88% 88% 44% 88% 88% 88% 88% 88% 88% 88% 88%
Tobruk 0% 0% 0% 0% 66% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88%
Proposed Steam Tripoli East 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Tobruk 2 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Derna 2 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Benghazi West 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Gas Sabha 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Tripoli South 2 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
CC Misurata 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Mellitah 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Zweitina 2 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Tobruk 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Aboukammash 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
BEST case Technical availability
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Type of plant Power Station 8 7 10 17 21 20 20 24 25 26 28 27 29 29 25
Existing Various Small / rented 0% 4% 53% 81% 91% 91% 91% 91% 91% 85% 85% 85% 85% 85% 85%
Steam Khoms 91% 80% 80% 85% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 0%
Derna 1% 0% 0% 50% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 0%
Tobruk 32% 0% 0% 50% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 0%
Misurata Steel 0% 12% 24% 90% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 0%
Gulf 44% 0% 43% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%
Tripoli West 0% 0% 0% 100% 100% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Benghazi North 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
Gas Tripoli South 90% 80% 85% 85% 85% 85% 85% 85% 85% 85% 88% 88% 88% 88% 88%
Zwetina 39% 33% 33% 85% 85% 85% 85% 85% 85% 85% 85% 85% 85% 85% 85%
Khoms 1 93% 82% 87% 87% 87% 87% 87% 87% 87% 87% 87% 0% 0% 0% 0%
Western Mountain 89% 72% 83% 83% 83% 83% 83% 83% 83% 83% 83% 83% 83% 83% 83%
Sarir 38% 22% 44% 53% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80%
Khoms 2 (Fast Track) 0% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95% 95%
CC Zawia 80% 68% 79% 79% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88%
Benghazi North 1 30% 38% 74% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88%
Misurata 92% 45% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88%
Benghazi North 2 81% 69% 85% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88%
Under contr. Steam Gulf 0% 0% 0% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%
/ contracted Tripoli West 0% 0% 0% 88% 88% 92% 87% 96% 96% 96% 96% 96% 96% 96% 96%
Tripoli East 0% 0% 0% 0% 88% 88% 44% 88% 88% 88% 88% 88% 88% 88% 88%
Gas Ubari 0% 0% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80% 80%
Misurata 0% 0% 0% 0% 88% 88% 44% 88% 88% 88% 88% 88% 88% 88% 88%
Tobruk 0% 0% 0% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88% 88%
Proposed Steam Tripoli East 0% 0% 0% 0% 0% 0% 0% 100% 100% 100% 100% 100% 100% 100% 100%
Tobruk 2 0% 0% 0% 0% 0% 0% 0% 0% 0% 100% 100% 100% 100% 100% 100%
Derna 2 0% 0% 0% 0% 0% 0% 0% 100% 100% 100% 100% 100% 100% 100% 100%
Benghazi West 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 100% 100% 100% 100% 100%
Gas Sabha 0% 0% 0% 0% 0% 0% 80% 80% 80% 80% 80% 80% 80% 80% 80%
Tripoli South 2 0% 0% 0% 0% 0% 0% 0% 88% 88% 88% 88% 88% 88% 88% 88%
CC Misurata 0% 0% 0% 0% 0% 0% 0% 0% 88% 88% 88% 88% 88% 88% 88%
Mellitah 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 88% 88% 88% 88% 88%
Zweitina 2 0% 0% 0% 0% 0% 0% 0% 0% 0% 88% 88% 88% 88% 88% 88%
Tobruk 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 88% 88% 88%
Aboukammash 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 88% 88% 88%
- 5 -
WORST case Thermal effciency - gas production
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Type of plant Power Station 31% 30% 31% 30% 30% 30% 30% 29% 29% 29% 29% 29% 29% 29% 29%
Existing Various Small / rented 10% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21%
Steam Khoms 20% 21% 21% 21% 21% 21%
Derna
Tobruk
Misurata Steel 31% 31% 31% 31% 31% 31% 31% 31% 31%
Gulf 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21%
Tripoli West 21% 21% 21% 21% 21%
Benghazi North 21% 21%
Gas Tripoli South 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28%
Zwetina 31% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32%
Khoms 1 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29%
Western Mountain 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31%
Sarir
Khoms 2 (Fast Track) 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30%
CC Zawia 45% 45% 45% 45% 45% 45% 45% 45% 45% 45% 45% 45% 45% 45% 45%
Benghazi North 1 46% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41%
Misurata 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49%
Benghazi North 2 46% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31%
Under contr. Steam Gulf 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21%
/ contracted Tripoli West 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21%
Tripoli East 21% 21% 21% 21% 21% 21% 21% 21% 21% 21% 21%
Gas Ubari 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30%
Misurata 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30%
Tobruk 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30%
Proposed Steam Tripoli East
Tobruk 2
Derna 2
Benghazi West
Gas Sabha
Tripoli South 2
CC Misurata
Mellitah
Zweitina 2
Tobruk
Aboukammash
BEST case
Type of plant Power Station 31% 33% 33% 33% 33% 33% 33% 33% 34% 34% 35% 35% 36% 37% 37%
Existing Various Small / rented 10% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32%
Steam Khoms 20% 23% 23% 23% 23% 23% 23% 23% 23% 23% 23% 23% 23% 23%
Derna
Tobruk
Misurata Steel 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31%
Gulf 21% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31%
Tripoli West 31% 31% 31% 31% 31%
Benghazi North 31% 31%
Gas Tripoli South 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28%
Zwetina 31% 35% 35% 35% 35% 35% 35% 35% 35% 35% 35% 35% 35% 35% 35%
Khoms 1 29% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30%
Western Mountain 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31%
Sarir
Khoms 2 (Fast Track) 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37%
CC Zawia 45% 47% 47% 47% 47% 47% 47% 47% 47% 47% 47% 47% 47% 47% 47%
Benghazi North 1 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46%
Misurata 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49% 49%
Benghazi North 2 46% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34%
Under contr. Steam Gulf 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31%
/ contracted Tripoli West 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31%
Tripoli East 31% 31% 31% 31% 31% 31% 31% 31% 31% 31% 31%
Gas Ubari 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37%
Misurata 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37%
Tobruk 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37% 37%
Proposed Steam Tripoli East 31% 31% 31% 31% 31% 31% 31% 31%
Tobruk 2 31% 31% 31% 31% 31% 31%
Derna 2 31% 31% 31% 31% 31% 31% 31% 31%
Benghazi West 31% 31% 31% 31% 31%
Gas Sabha 37% 37% 37% 37% 37% 37% 37% 37% 37%
Tripoli South 2 37% 37% 37% 37% 37% 37% 37% 37%
CC Misurata 49% 49% 49% 49% 49% 49% 49%
Mellitah 49% 49% 49% 49% 49%
Zweitina 2 49% 49% 49% 49% 49% 49%
Tobruk 49% 49% 49%
Aboukammash 49% 49% 49%
- 6 -
WORST case Thermal effciency - oil production
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Type of plant Power Station 24% 28% 28% 28% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27%
Existing Various Small / rented 23% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24%
Steam Khoms 29% 29% 29% 29% 29% 29%
Derna 19% 23%
Tobruk 24% 17%
Misurata Steel 20% 22% 22% 22% 22% 22% 22% 22% 22%
Gulf 30% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32% 32%
Tripoli West 24% 24% 24% 24% 24%
Benghazi North 24% 24%
Gas Tripoli South 28% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26%
Zwetina 24% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25%
Khoms 1 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28%
Western Mountain 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28%
Sarir 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27%
Khoms 2 (Fast Track) 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27%
CC Zawia 40% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41%
Benghazi North 1 31% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28%
Misurata 32% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41% 41%
Benghazi North 2
Under contr. Steam Gulf 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24%
/ contracted Tripoli West 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24%
Tripoli East 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24%
Gas Ubari 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27%
Misurata 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27%
Tobruk 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27% 27%
Proposed Steam Tripoli East
Tobruk 2
Derna 2
Benghazi West
Gas Sabha
Tripoli South 2
CC Misurata
Mellitah
Zweitina 2
Tobruk
Aboukammash
BEST case Thermal effciency - oil production
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Type of plant Power Station 25% 31% 31% 31% 31% 31% 31% 31% 32% 32% 33% 33% 34% 35% 35%
Existing Various Small / rented 23% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33%
Steam Khoms 29% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30%
Derna 19% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29%
Tobruk 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24% 24%
Misurata Steel 20% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26%
Gulf 30% 36% 36% 36% 36% 36% 36% 36% 36% 36% 36% 36% 36% 36% 36%
Tripoli West 33% 33% 33% 33% 33%
Benghazi North 33% 33%
Gas Tripoli South 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28% 28%
Zwetina 24% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26% 26%
Khoms 1 28% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30%
Western Mountain 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29% 29%
Sarir 27% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30%
Khoms 2 (Fast Track) 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30%
CC Zawia 40% 43% 43% 43% 43% 43% 43% 43% 43% 43% 43% 43% 43% 43% 43%
Benghazi North 1 31% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34% 34%
Misurata 32% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46% 46%
Benghazi North 2
Under contr. Steam Gulf 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33%
/ contracted Tripoli West 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33%
Tripoli East 33% 33% 33% 33% 33% 33% 33% 33% 33% 33% 33%
Gas Ubari 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30%
Misurata 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30%
Tobruk 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30% 30%
Proposed Steam Tripoli East 33% 33% 33% 33% 33% 33% 33% 33%
Tobruk 2 33% 33% 33% 33% 33% 33%
Derna 2 33% 33% 33% 33% 33% 33% 33% 33%
Benghazi West 33% 33% 33% 33% 33%
Gas Sabha 30% 30% 30% 30% 30% 30% 30% 30% 30%
Tripoli South 2 30% 30% 30% 30% 30% 30% 30% 30%
CC Misurata 46% 46% 46% 46% 46% 46% 46%
Mellitah 46% 46% 46% 46% 46%
Zweitina 2 46% 46% 46% 46% 46% 46%
Tobruk 46% 46% 46%
Aboukammash 46% 46% 46%
Libya - Supporting Electricity Sector Reform (P154606)
Contract No. 7181909 - Task D: Strategic Plan for Renewable Energy Development
Least Cost Expansion Plan (LCEP) Annex VI – Cost of Capital Assumptions 12th December 2017
Client:
The World Bank
1818 H Street, N.W.
Washington, DC 20433
Consultant:
GOPA-International Energy Consultants GmbH
Justus-von-Liebig-Str. 1, 61352 Bad Homburg, Germany
Phone: +49-6172-1791-800; Fax: +49-6172-944 95 20
eMail: info@gopa-intec.de; www.gopa-intec.de
Suntrace GmbH
Grosse Elbstrasse 145c, 22767 Hamburg, Germany
Phone: +49-40-767 96 38 0; Fax: +49-40-767 96 38 20
www.suntrace.de
Libya SPREL – LCEP Report – Annex VI Cost of Capital Assumptions
LBY2560_TaskD_ StageI_LCEP_Report_AnnexVI_CostCapitalAssumptions.docx
Table of Contents Page
1. Cost of Capital Assumptions 2
- 2 -
Libya SPREL – LCEP Report – Annex VI Cost of Capital Assumptions
LBY2560_TaskD_ StageI_LCEP_Report_AnnexVI_CostCapitalAssumptions.docx
1. Cost of Capital Assumptions
For the estimation of total CAPEX and other economic estimations in this assignment, the Consultant
made the assumptions set out below.
Item Unit PV CSP Wind
Leverage % 70 70 70
Interest Base Rate % 5 2 5
Discount rate % 15 15 15
WACC % 8 6 8
Depreciation time a 25 30 25
Construction time a 0.5 2 0.6
Table 1-1: Economic and financial assumptions for cost of capital
According to discussions among the stakeholders carbon price will not play a role within this assign-
ment.
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