Embed Size (px)
Citation preview
© OECD/IEA 2014
Renewables Grid Integration and Variability Session 1: Introduction, variable generation, flexibility and netload
IEA Training and Capacity Building - Latin America, Santiago de Chile, 10-14 Nov 2014
© OECD/IEA 2014
Session 1: Introduction, variable generation, flexibility, netload Excurse: Flexible Generation from coal? Excercise: Net load analysis (after coffee in different room)
Session 2: System impacts and adapting operations Excercise: Reserve requirements and VRE forecasts
Session 3: Economics of grid integration, system transformation Excercise: The value of variable generation
Course overview
© OECD/IEA 2014 2
© OECD/IEA 2014
Session 1: Introduction, variable generation, flexibility, netload
1. Identifying relevant questions and issues
2. Grid based power systems: generation, transmission, distribution, loads
3. Relevance of balancing supply and demand across different time scales
4. 6 properties of variable renewable energy (VRE)
5. 4 sources of power system flexibility Flexible Generation from coal?
6. Variable renewables as negative loads – the concept of net load
Exercise 1: Constructing net load for different shares of wind and PV
Analysing net load ramps
Average vs. Instantaneous penetration
Session agenda
© OECD/IEA 2014 3
© OECD/IEA 2014
Relevant questions and issues?
© OECD/IEA 2014 4
© OECD/IEA 2014
Some basics
© OECD/IEA 2014 5
© OECD/IEA 2014
Grid based power systems are historically been organised into generation, transmission and distribution
This is still main paradigm for most systems
Grid based power systems
© OECD/IEA 2014 6
© OECD/IEA 2014
Power demand varies by region, season and daytime
© OECD/IEA 2014 7
© OECD/IEA 2014
Why is it challenging to balance supply and demand of electricity? What are relevant time scales?
© OECD/IEA 2014 8
© OECD/IEA 2014
Properties of VRE
© OECD/IEA 2014 9
© OECD/IEA 2014
The 6 VRE properties that matter
Variable Maximum output varies depending on wind and sunlight
Uncertain No perfect forecast for wind and sunlight available
Non-synchronous technologies VRE connect to grid via power electronics, have little or no
rotating mass
Location constrained resource is not equally good in all locations and cannot be
transported
Modularity Wide range of sizes and may be much smaller than other options
Low short-run cost Once built, VRE generate power almost for free
sec
yrs
1km
100s km
© OECD/IEA 2014 10
© OECD/IEA 2014
Variability: Examples of solar PV and wind
© OECD/IEA 2014 11
© OECD/IEA 2014
Examples of wind and solar PV
© OECD/IEA 2014 12
© OECD/IEA 2014
Uncertainty reduces dramatically with shorter horizon
Real-time generation data key for short-term accuracy
Forecasts generally more mature for wind than for PV
Uncertainty
© OECD/IEA 2014 13
0%
5%
10%
15%
20%
25%
1 5 9 13 17 21 25 29 33 37 41 45
Mea
n a
bso
lute
err
or
/ av
erag
e p
rod
uct
ion
Forecast horizon (Hours before real-time)
2008 2009
2010 2011
2012
Accuracy of wind forecasts in Spain
Source: REE
© OECD/IEA 2014
Excurse: Non-synchronous generation
© OECD/IEA 2014 14
Source:Characteristics of Wind Turbine Generators for Wind Power PlantsIEEE PES Wind Plant Collecto System Design Working Group
© OECD/IEA 2014
Netload and flexibility
© OECD/IEA 2014 15
© OECD/IEA 2014
Netload = Load - VRE
Note: Load data and wind data from Germany 10 to 16 November 2010, wind generation scaled, actual share 7.3%. Scaling may overestimate the impact of variability; combined effect of wind and solar may be lower, illustration only.
© OECD/IEA 2014 16
0
10
20
30
40
50
60
70
80
1 10 20 30 40 50 60 70 80 90 100 110 120 130 140 Hours
Net
load
(G
W)
0.0% 2.5% 5.0% 10.0% 20.0%
Illustration of netload at different VRE shares
© OECD/IEA 2014
Four sources of flexibility …
Grid infrastructure
Dispatchable generation Storage
Demand side integration
© OECD/IEA 2014 17
© OECD/IEA 2014
What is flexibility?
Definition “Extent to which a power system can adjust the balance of electricity
production and consumption in response to variability, expected or otherwise.”
Measurement of
Flexibility supply
Flexibility demand
Comparison of supply and demand
Flexibility options may Increase supply
Reduce demand
© OECD/IEA 2014
Extent of adjustment
Maximum change of supply/demand balance over a certain time horizon
Two scales [+/-MW] per time horizon
But capability will depend on:
Past system state
Current system states
Future system state
VERY many dimensions
This gives rise to complex effects that make mapping of a system on above scales challenging
Operationalization of technical flexibility
© OECD/IEA 2014
Capable of: “Achieving and sustaining any consumption or generation level at arbitrarily small response times at no cost.”
Relevant dimensions?
Possible levels: “Adjustability”
Max. duration of output: ”Durability”
Possible changes: “Ramping”
“Lead time” for change
“State dependency”
Real power sources, loads & storage approximate ideal source on these dimensions
Looking at the ideal power device
Handful of relevant time scales
© OECD/IEA 2014
Flexible generation: Conventional plants and firm RE adjustable in wide range, very durable,
more or less rampable, different lead time and state dependency (nuclear to OCGT)
Adjustability and durability of varRE limited by resource, but within these bounds they are very rampable, little response time, almost no state dependency
DSM Adjustable (consumption), varying durability, varying rampable, lead
time, possibly high state dependency
Storage Perfect adjustability, determined durability …
Interconnection Can reduce demand and increase supply along all dimensions
The 4 flexible resources
© OECD/IEA 2014
Focus on flexible generation
Or: can a coal plant really ramp?
© OECD/IEA 2014 22
© OECD/IEA 2014
German hard coal plants carry most of ramping duty in Germany Lignite and nuclear ramp as well, even nuclear at some times
Ramping costs can be minimised at low cost; retrofits are possible e.g. Flexible Coal: Evolution from Baseload to Peaking Plant (NREL, 2013)
Flexibility: ask for it…. and it appears
© OECD/IEA 2014 23
A sunny 1st May 2013 in Germany – actual production
Source: Fraunhofer ISE
© OECD/IEA 2014
Experiences from coal in Denmark
© OECD/IEA 2014 24
© OECD/IEA 2014
It‘s not the fuel – it‘s the design and the operation
© OECD/IEA 2014 25
© OECD/IEA 2014
Power systems already deal with a vast demand variability Can use existing flexibility for VRE integration
No problem at low shares, because …
© OECD/IEA 2014 26
Exceptionally high variability in Brazil, 28 June 2010
© OECD/IEA 2014
Exercise 1: Netload
© OECD/IEA 2014 27
© OECD/IEA 2014
Session 2: System impacts and adapting operations
1. Overview of impact groups
2. Avoiding typical mistakes when beginning deployment
3. Focus on balancing
4. Focus on utilisation
5. Focus on grids
6. Specific challenges and opportunities of distributed, small-scale PV
7. Strategies for improving system operations
Exercise 2: Calculate impact of scheduling intervals on reserve requirements
Assess benefit of using close to real-time forecast data
Session agenda
© OECD/IEA 2014 28
© OECD/IEA 2014
Different impact groups
© OECD/IEA 2014 29
© OECD/IEA 2014
Interaction is key
Properties of variable renewable energy (VRE)
Flexibility of other power system components
© OECD/IEA 2014 30
Variable
Uncertain
Non-synchronous
Location constrained
Modularity
Low short-run cost
sec
yrs
1 km
100s km
Grids Generation
Storage Demand Side
© OECD/IEA 2014
Seconds Years 100km 1km
Low short run cost
Non synchro-
nous
Stability
Uncertainty
Reserves
Variability
Short term changes
Asset
utilisation
Abundance Scarcity
Location constrained
Trans-mission
grid
Modularity
Distribution grid
Properties of variable renewables and impact groups
Systems are different – impacts will vary too
But common groups of effects
© OECD/IEA 2014 31
Balancing Profile / Utilisation Location Stability
© OECD/IEA 2014
Issues investigated in integration studies
© OECD/IEA 2014 32
Time-constant/Period time
1ms 10ms 100ms 1s 1hr 1 day years
Power Quality (Harmonics,
Electromagnetic Transients)
Fault Current Level &
Protection
Transient Voltage Stability (LVRT)
Congestion Management (Transmission
Efficiency)
Electro- mechanical Stability (Rotor Angle Stability, Small Signal Stability,
Sub-Synchronous Resonance)
Tertiary Reserve
(Unit Commitment & Replacement
Reserve & Network Control
Reserve)
CO2 & Fuel Prices
Generation Adequacy
Grid Adequacy
1min 1 month
Dispatch Balancing
loca
l re
gio
nal
sy
stem
wid
e
• Australia (NEM)
• Iberia (REE & REN)
• Texas (ERCOT)
• Hydro Québec
• Ireland (All Island)
• Germany (DENA)
• New Zealand (Transpower)
MOST RELEVANT SYSTEM STUDIES Secondary
Reserve (AGC
Regulation)
Planning Operation
Security
Source: Dr Thomas Ackermann, Energynautics
© OECD/IEA 2014
IEA Wind Implementing Agreement Task 25: Design and Operation of Power Systems with Large Amounts of Wind Power
http://www.ieawind.org/index_page_postings/100313/RP%2016%20Wind%20Integration%20Studies_Approved%20091213.pdf
Grid integration studies – best practice
© OECD/IEA 2014 33
© OECD/IEA 2014
Persistent impacts
© OECD/IEA 2014 34
© OECD/IEA 2014
1. Excessive geographic, technical concentration
Key lessons: analysis based diversification of location and technology
2. Ill-adapted technical performance standards
Key lessons: focus on grid codes! (fault ride through, 50.2 Hertz); visibility and controllability
3. No or ineffective VRE production forecasts
Key lessons: use forecasts in unit commitment and dispatch of other generation
Three typical mistakes to avoid when deployment begins
© OECD/IEA 2014 35
© OECD/IEA 2014
There is no single factor that would put a maximum technical limit on the long-term amount of variable generation
However, more and more measures are needed to achieve high shares
In the short term, many institutional and some technical issues can be a constraint.
Question rather is: How far can I go before it get‘s expensive? And what do I need to do for that?
No principal technical limit on VRE share
© OECD/IEA 2014 36
What is the maximum speed at which you can driver a car?*
*Apart from the speed of light
© OECD/IEA 2014
Main persistent challenge: Balancing
Note: Load data and wind data from Germany 10 to 16 November 2010, wind generation scaled, actual share 7.3%. Scaling may overestimate the impact of variability; combined effect of wind and solar may be lower, illustration only.
© OECD/IEA 2014 37
0
10
20
30
40
50
60
70
80
1 10 20 30 40 50 60 70 80 90 100 110 120 130 140 Hours
Net
load
(G
W)
0.0% 2.5% 5.0% 10.0% 20.0%
Larger ramps at high shares
Higher uncertainty
Larger and more pronounced changes
Illustration of Residual power demand at different VRE shares
Lower minimum
© OECD/IEA 2014
VRE impact – hourly values (MW)
Load PV
Wind Netload
Hourly values in MW for different times of a day and days of a year in Spain and Portugal
Note: figures refer to year 2011
© OECD/IEA 2014
VRE impact – hourly differences (MW)
Load PV
Wind Netload
Hourly differences in MW for different times of a day and days of a year in Spain and Portugal
Note: figures refer to year 2011
© OECD/IEA 2014
Netload implies different utilisation for non-VRE system
Main persistent challenge: Utilisation
Note: Load data and wind data from Germany 10 to 16 November 2010, wind generation scaled, actual share 7.3%. Scaling may overestimate the impact of variability; combined effect of wind and solar may be lower, illustration only.
© OECD/IEA 2014 40
0
10
20
30
40
50
60
70
80
90
1 2 000 4 000 6 000 8 000
Net
load
(G
W)
Hours
0.0% 2.5% 5.0% 10.0% 20.0% Maximum
remains high: Scarcity
Lower minimum:
Abundance
Changed utilisation pattern
Base - load
Mid - merit
Peak
Mid - merit
Peak
Mid - merit
Base - load
-
-
© OECD/IEA 2014
Voltage rise common issue
Smart inverters and transformers help
Distributed PV and the grid 1/2
© OECD/IEA 2014 41
Vo
ltag
e le
vel d
evia
tio
n
Transformer
Transformer
O%
+9%
Voltage rise in a rural distribution system in Germany
© OECD/IEA 2014
Reverse flows no big technical issue
But too high concentration can imply costly retrofits
Distributed PV and the grid 2/2
Power flows across HV-MV transformer example form Bavaria, Germany
Source: Bayernwerk, Fraunhofer IWES From Transmission to Distribution
From Distribution to Transmission
© OECD/IEA 2014
Competitive Renewable Energy Zones (CREZ), Texas
Wind built before completing all transmission lines
Curtailment peaked at 17% in 2009
Curtailment reduced to 1.6% in 2013 after implementing locational pricing and expanding the grid
Wind in Texas – Operational issues while waiting on transmission
© OECD/IEA 2014 43
345 kV double-circuit upgrades identified in
CREZ transmission plan
CREZ, Texas
Source: NREL
© OECD/IEA 2014 26/27 January 2013
Excurse: Maximum penetration levels
© OECD/IEA 2014 44
© OECD/IEA 2014
Maximum non-synchronous penetration in Ireland
© OECD/IEA 2014 45
WMAX
SMAX
WMIN
SMIN
W0 W25 W50 W75 W100
http://www.eirgrid.com/media/Renewable%20Studies%20V3.pdf
© OECD/IEA 2014
Adapting operations
© OECD/IEA 2014 46
© OECD/IEA 2014
Forecasting of VRE production key strategy for cost-effective operation
But operations need to make use of them:
Adjust schedules to incorporate newest information
Allows to extract all available flexibility
VRE production forecasts
© OECD/IEA 2014 47
0%
5%
10%
15%
20%
25%
1 5 9 13 17 21 25 29 33 37 41 45
Mea
n a
bso
lute
err
or
/ av
erag
e p
rod
uct
ion
Forecast horizon (Hours before real-time)
2008 2009
2010 2011
2012
Accuracy of wind forecasts in Spain
Source: REE
© OECD/IEA 2014
Short scheduling intervals (5min best practice)
Adjust schedules up to real time (5min best practice)
Generation and transmission schedules
© OECD/IEA 2014 48
6 7 8 9
Cap
acit
y (M
W)
Time (hours)
Actual load curve
Load schedule -15 minutes
Load schedule -60 minutes
Balancing need 15 min schedule
Balancing need60 min schedule
Impact of scheduling interval on reserve requirements, illustration
© OECD/IEA 2014
Germany has four balancing areas (historic reasons)
Reserve sharing mechanism across four areas
Reduced requirements despite rapid increase of VRE
Co-operation with neighbours
© OECD/IEA 2014 49
0
10
20
30
40
50
60
0
1
2
3
4
5
6
7
8
2008 2009 2010 2011 2012
Inst
alle
d V
RE
cap
acit
y (G
W)
Res
erve
req
uir
emen
t (G
W) VRE
capacity
Upward reserves
Downward reserves
+100%
+0%
-40%
Required frequency restoration reserves in Germany
© OECD/IEA 2014
Are your operating reserve and system service definitions VRE ready?
Example Ireland DS3 programme
System service definitions Prepared for a variable future?
© OECD/IEA 2014 50
• Synchronous Inertial Response• Fast Frequency Response• Fast Post-Fault Active Power
Recovery
• Ramping Margin
0 – 5s 5 – 90s 90s – 20min 20min – 12hr
Inertial
Response
Reserve
Ramping
POR
SOR
TOR1
TOR2
RR
Ramping
SIR
FFR
time
Source: EirGrid • Dynamic Reactive Power
ms – s
Transient Voltage Response
Voltage Regulation
Network
Dynamic
Reactive
Power
Network
Adequacy
Grid 25
s – min min – hr
Steady-state
Reactive
Power
• Steady-state Reactive Power
Frequency Services
Voltage Services
© OECD/IEA 2014
Exercise 2: Reserve requirements and VRE forecasts
© OECD/IEA 2014 51
© OECD/IEA 2014
Session 3: System friendly VRE, economics of grid integration, system transformation 1. Options for system friendly VRE deployment
2. Market fundamentals: stable and dynamic power systems,
3. Merit-order effect and utilisation effect
4. System costs and system value of variable generation
5. Economic analysis of the four flexible resources
6. System transformation and total system costs
Exercise 3: Calculate total system costs in a system where VRE are just added
Calculate total system costs in a system where VRE and other plants can be matched to each other
Session agenda
© OECD/IEA 2014 52
© OECD/IEA 2014
System friendly VRE
© OECD/IEA 2014 53
© OECD/IEA 2014
Economics of VRE integration
© OECD/IEA 2014 58
© OECD/IEA 2014
* Compound annual average growth rate 2012-20 , slow <2%, dynamic ≥2%; region average used where country data unavailable This map is without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area.
Transformation depends on context
© OECD/IEA 2014 59
Stable Power Systems
• Sluggish demand growth • Little general investment needed short-term Example: Europe
Dynamic Power Systems
• Dynamic demand growth • Large general investment needed short-term Example: Emerging economies
Slow demand growth*
Dynamic demand growth*
© OECD/IEA 2014
Main market impacts in stable systems
Reduced market prices (merit order effect)
Reduced operating hours (utilisation effect)
Displacement effect mainly due to
low short-run cost of VRE and
reinforced by support policies
influenced by variability, in particular PV
Economic impact on gas generation result of several factors
Shift in German spot market price structure
© OECD/IEA 2014 60
© OECD/IEA 2014
The ‘merit order effect’
© OECD/IEA 2014 61
© OECD/IEA 2014
Netload implies different utilisation for non-VRE system
Main persistent challenge: Utilisation
Note: Load data and wind data from Germany 10 to 16 November 2010, wind generation scaled, actual share 7.3%. Scaling may overestimate the impact of variability; combined effect of wind and solar may be lower, illustration only.
© OECD/IEA 2014 62
0
10
20
30
40
50
60
70
80
90
1 2 000 4 000 6 000 8 000
Net
load
(G
W)
Hours
0.0% 2.5% 5.0% 10.0% 20.0% Maximum
remains high: Scarcity
Lower minimum:
Abundance
Changed utilisation pattern
Base - load
Mid - merit
Peak
Mid - merit
Peak
Mid - merit
Base - load
-
-
© OECD/IEA 2014
Displacement of units with highest operating costs
Utilisation: short term impact
© OECD/IEA 2014 63
0
10
20
30
40
50
60
70
80
90
1 2 000 4 000 6 000 8 000
Net
load
(G
W)
Hours
Peak Mid-merit Base
© OECD/IEA 2014
Re-adaptation leads to displacement of technologies that are costly at low utilisation rates
Utilisation: long term impact
© OECD/IEA 2014 64
0
10
20
30
40
50
60
70
80
90
1 2 000 4 000 6 000 8 000
Net
load
(G
W)
Hours
Peak Mid-merit Base
© OECD/IEA 2014
At growing shares of variable generation, cost savings in the residual system tend to slow
(Most) relevant economic effect, exact numbers system specific
Not captures by standard ‘back-up costs’
Impacts of utilisation on total costs of residual system
© OECD/IEA 2014 66
15
20
25
30
35
100% 90% 80% 70% 60%
Total c
ost (billion US
D/year)
Remaining net load
Solar PV only
Wind only
Mix
Baseload
Benchmark
© OECD/IEA 2014
Modelled balancing costs are usually in the order of a few USD/MWh, highly system dependent, typically rise with VRE share
Empirical data from German market: approx. 3 EUR/MWh to balance the FIT-portfolio
Examples of calculating balancing costs
© OECD/IEA 2014 67
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
0% 5% 10% 15% 20% 25% 30%
USD/
MWh of w
ind
Wind penetration as share of gross demand
Ireland (SEAI)UK, 2002UK, 2007Colorado USMinnesota 2004Minnesota 2006California USEWITS, USPacificorp USGreennet SwedenGreennet NorwayGreennet DenmarkGreennet FinlandGreennet Germany
© OECD/IEA 2014
Investment in additional flexibility
Grid infrastructure
Dispatchable generation Storage
Demand side integration
Four sources of flexibility …
© OECD/IEA 2014 68
© OECD/IEA 2014
Flexibility options - Transmission Where do you get inexpensive flexibility?
© OECD/IEA 2014 69
Interconnection can offer low-cost flexibility
© OECD/IEA 2014
Flexibility options – Electricity Storage Where do you get inexpensive flexibility?
© OECD/IEA 2014 70
Storage shows relatively high LCOF compared to other options
But not only costs count – also the value matters
© OECD/IEA 2014
Flexibility options – DSI Where do you get inexpensive flexibility?
© OECD/IEA 2014 71
DSI potentially very favourable benefit/cost ratio
Moving demand to when wind blows and sun shines increases firm capacity credit of variable sources
But what is the real potential?
© OECD/IEA 2014
Flexibility options – Generation Where do you get inexpensive flexibility?
© OECD/IEA 2014 72
© OECD/IEA 2014
Benefit/cost of flexibility options North West Europe - DSI
Overall system savings of 2.0 bln $/year
DSI costs of 0.9 bln $/year
Note: graph represents the differences between DSI scenario (DSI 8% of overall demand) and baseline scenario
Benefit/cost ratio: 2.2
© OECD/IEA 2014 73
-29 -140-437
-1 539
899128
-2 500
-2 000
-1 500
-1 000
- 500
0
500
1 000
1 500
System benefit DSI costs
Mill
ion
USD
per
yea
r
DSI
Capex CCGT
Fixed Opex
Start up costs
Variable cost incl. fuel
CO2 costs
DSI assumed to be 8% of annual power demand:
• 71% made of heat and other schedulable demand (110 TWh)
• 29% EV demand (44 TWh)
CO2 price USD 30 per tonne Coal price USD 2.7/Mmbtu Gas price USD 8/Mmbtu
© OECD/IEA 2014
Benefit/cost of flexibility options North West Europe
DSI has large benefits at comparably low costs
Interconnection allows a more efficient use of distributed flexibility options and generates synergies with storage and DSI
Cost effectiveness of hydro plant retrofit depend on project specific measures and associated investment needs
Notes: 1) CAPEX assumed for selected flexibility options: interconnection 1,300$/MW/km onshore and 2,600$/MW/km offshore, pumped hydro storage 1,170$/kW, reservoir
hydro 750 $/kW -1,300$/kW (repowering of existing reservoir hydro increasing available capacity). Cost of DSI is assumed equal to 4.7 $/MWh of overall power demand (adjustment of NEWSIS results)
2) Fuel prices and CAPEX ($/kW) for VRE and flexibility options are assumed constant across all scenarios Source: IEA/PÖYRY
2.3 2.2
1.2 1.1 1.1
0.6 - 1.5
DSI + IC DSI IC Storage + IC Storage Hydro capacityboost
Benefit/cost ratio
1
© OECD/IEA 2014 74
© OECD/IEA 2014
-20
0
20
40
60
80
321 322 323 324 325 326 327
GW
Day of the year Wind Solar Demand Net load
Investments in system flexibility – Need for a suite of solutions
© OECD/IEA 2014 75
Solar and wind can be abundant …
… or scarce.
No single resource does it all!
: very suitable, :suitable, o : neutral, : unsuitable Data: Germany 2011, 3x actual wind and solar PV capacity
Example:
Abundance Flexible generation
DSI
Storage
Curtailment
Scarcity Flexible generation
DSI o
Storage
Curtailment
-20
0
20
40
60
80
33 34 35 36 37 38 39
GW
Day of the year Wind Solar Demand Net load
© OECD/IEA 2014
System transformation and total system costs
© OECD/IEA 2014 76
© OECD/IEA 2014
Integration vs. transformation
Classical view: VRE are integrated into the rest
Integration costs: balancing, adequacy, grid
More accurate view: entire system is re-optimised
Total system costs
Integration is actually about transformation
Remaining system
VRE
Power system
• Generation • Grids • Storage • Demand Side Integration
© OECD/IEA 2014 77
© OECD/IEA 2014
2. Make better use of
what you have
Op
eratio
ns
1. Let wind and solar play their
part
3. Take a system wide-strategic
approach to investments!
System friendly
VRE
Technology spread
Geographic spread
Design of power
plants
Three pillars of system transformation
© OECD/IEA 2014 78
Investm
ents
© OECD/IEA 2014
0
20
40
60
80
100
120
140
Legacy
low grid costs
Legacy
high grid costs
Transformed generation &
8% DSI, low grid costs
0% VRE
Tota
l sys
tem
co
sts
(USD
/MW
h)
Large shares of VRE can be integrated cost-effectively
Significant optimization on both fixed and variable costs
Cost-effective integration means transformation of power system
© OECD/IEA 2014 79
Test System / IMRES Model
45% VRE penetration
Grid cost
DSI
Fixed VRE
Emissions
Fuel
Startup
Fixed
non-VRE
+40%
+10-15%
© OECD/IEA 2014
Exercise 3: Effects of VRE on total system costs
© OECD/IEA 2014 80
© OECD/IEA 2014
Add-on: integration costs
© OECD/IEA 2014 81
© OECD/IEA 2014
Decomposition always challenging:
Balancing, adequacy, grids
Uncertainty, profile, location
Unclear that all effects are covered with these practices; categories not independent
Calculation requires reference technology:
Common benchmark for all technologies can skew the calculation (flat block benchmark) or miss important adaptation options (load correlated benchmark)
Portfolio of technologies (not just generation) needed to minimise total system costs.
Frequent classification
© OECD/IEA 2014 82
© OECD/IEA 2014
Decomposition always challenging:
Balancing, adequacy, grids
Uncertainty, profile, location
Unclear that all effects are covered with these practices; categories not independent
Calculation requires reference technology:
Common benchmark for all technologies can skew the calculation (flat block benchmark) or miss important adaptation options (load correlated benchmark)
Portfolio of technologies (not just generation) needed to minimise total system costs.
Problems with calculating integration costs
© OECD/IEA 2014 83
© OECD/IEA 2014
Alternative: System value
Benchmark VRE against net savings in residual power system – more useful than trying to calculate integration costs
System value depends on transformation of the system
System value LCOE
Saving
sCo
sts
Net savings in
residual system per
MWh of VRE
generation
Generation costs per
MWh of VRE
© OECD/IEA 2014 84
