57
Decarbonisation modelling in the electricity sector Montenegro Support for Low-Emission Development in South Eastern Europe (SLED)

Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

  • Upload
    others

  • View
    2

  • Download
    0

Embed Size (px)

Citation preview

Page 1: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Decarbonisation modelling in the electricity sector

Montenegro

Support for Low-Emission Development in South Eastern Europe (SLED)

MO

NTE

NEG

RO

EN

G

Page 2: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Decarbonisation modelling in the electricity sector

Montenegro

Authors

András Mezősi, PhD

László szabó, PhD

(Regional Centre for Energy Policy Research)

support for Low-Emission Development in south Eastern Europe (sLED)

December 2015

Page 3: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

AcknowLEDgEMEntsREC project management: József Feiler, Vaiva Indilaite, Ágnes kelemen, gordana kozhuharovaDesign and layout: tricia Barna, Juan tornerosCopyediting and proofreading: rachel hidegPublisher: the regional Environmental center for central and Eastern Europe (rEc)Photo credits: istock

The REC is implementing the project “Support for Low-Emission Development in South Eastern Europe”(SLED) to help policy makers in the project countries (Albania, the former Yugoslav Republic of Macedonia,Montenegro and Serbia) to establish realistic but ambitious decarbonisation pathways for their electricityand building sectors by 2030.

The SLED project is funded by the Austrian Development Cooperation through the Austrian DevelopmentAgency (ADA). Special thanks are due to Hubert Neuwirth and Monika Tortschanoff of ADA.

Page 4: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Table of contents

I. ExEcutIVE suMMAry 6

II. IntroDuctIon 10

III. MEthoDoLogy 12

Scenario development framework 13

Models 14 The European Electricity Market Model 14

The EKC network model 15

Model assumptions 16 Cross-border network capacities 16

Current generation capacities 17

Fossil fuel prices 17

European Union Emissions Trading System price 17

European Union minimum tax levels for energy products 17

IV. scEnArIo AssuMPtIons 19

Introduction of the European Union Emissions Trading System 21

Introduction of minimum excise duty on energy products 21

Environmental standards enforcement 21

Deployment of renewable energy sources for electricity 21

Conventional power plants 21

Electricity demand 23

V. MoDELLIng rEsuLts 24

Price development 25

Regional outlook 26

Generation mix 28

CO₂ impacts 28

Net import position 30

Investment costs 31

Support budget for renewable energy sources for electricity 32

VI. sEnsItIVIty AssEssMEnt 36

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 3

Page 5: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro4

VII. nEtwork IMPActs 40

Planned new network elements 42

Results of network modelling 43 Steady-state and contingency analyses 43

System balances 44

(N-1) Security criteria 44

Net transfer capacity 45

Transmission grid losses 48

VIII. AnnEx 49

The European Electricity Market Model 50 Geographical scope 51

Market participants 51

Equilibrium 52

Network representation 53

The EKC network model 53 Load-flow data collection 53

Demand 54

Network modelling methodology 54 Steady-state and contingency analyses 54

Evaluation of net transfer capacity 54

Transmission grid losses 55

Page 6: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 5

Tables and figuresTable 1 Present net transfer capacity values in the region (MW) 17

Table 2 Planned interconnectors and their investment status (MW) 18

Table 3 Electricity generation capacities, 2014 18

Table 4 Fuel prices, 2015–2030 18

Table 5 Main scenario assumptions for Montenegro 20

Table 6 Capacity deployment of renewable energy sources for electricity in the scenarios (MW) 22

Table 7 Gross electricity consumption in Montenegro (GWh) 23

Table 8 Cumulated investment costs in 2015–2030 in the three scenarios 34

Table 9 Contingencies in 2020 43

Table 10 Contingencies in 2025 44

Table 11 Transmission losses in 2015, 2020 and 2025 for Montenegro, for all scenarios and regimes 48

Executive summary Figure 1 Generation mix, net imports and CO2 emissions in the three scenarios 8

Executive summary Figure 2 Tax-based revenues and expenditures on RES-E support 9

Figure 1 Modelled countries 15

Figure 2 Base-load price evolution in the various scenarios (EUR/MWh) 25

Figure 3 Peak-load price evolution in the various scenarios (EUR/MWh) 26

Figure 4 Planned new fossil fuel–based capacities South Eastern Europe, 2015–2030 27

Figure 5 Planned new renewables-based capacities in South Eastern Europe, 2015–2030 27

Figure 6 Generation mix, net imports and CO₂ emissions in the three scenarios 28

Figure 7 CO₂ emission levels per capita 29

Figure 8 CO₂ intensity of electricity consumption (tCO₂/GWh) 30

Figure 9 CO₂ intensity of electricity production (tCO₂/GWh) 31

Figure 10 Revenues from the Emissions Trading System and excise tax 32

Figure 11 Net import position changes in Montenegro in the three scenarios 33

Figure 12 Annual support budget for renewable energy sources for electricity (EUR million) 34

Figure 13 Average support for renewable energy sources for electricity from end consumers (EUR/MWh) 34

Figure 14 Change in the electricity mix in the case of low hydro availability 37

Figure 15 Changes in the net import position of Montenegro 38

Figure 16 Base-load price changes in Montenegro (EUR/MWh) 39

Figure 17 Geographical coverage of the network analysis 41

Figure 18 Planned interconnection lines in South Eastern Europe 42

Figure 19 Net transfer capacity values for 2020 (winter regime) 46

Figure 20 Net transfer capacity values for 2020 (summer regime) 46

Figure 21 Net transfer capcity values for 2025 (winter regime) 47

Figure 22 Net transfer capcity values for 2025 (summer regime) 47

Figure 23 Annual transmission losses in Montenegro for all scenarios 48

Figure 24 Analysed countries 50

Figure 25 Operation of the model 52

Page 7: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

I. Executive summary

Page 8: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 7

The objective of the project “Support for Low-Emission Development in South Eastern Europe(SLED)” is to help policy makers in Albania, the formerYugoslav Republic of Macedonia, Montenegro andSerbia) to set realistic but ambitious decarbonisationpathways for their electricity sectors up to 2030. Inthe case of Montenegro, the project results were alsoused in the assessment process for the country’s in-tended nationally determined contributions (INDC).

This study assesses the effect of decarbonisation sce-narios on the Montenegrin electricity system.

The scenarios (Reference – REF; Currently PlannedPolicies – CPP; and Ambitious – AMB) use different as-sumptions related to electricity demand and supply.Supply-side factors include the deployment levels ofrenewable energy sources for electricity (RES-E), thefirst year of operation of the planned Pljevlja II powerplant and its biomass co-firing rate, and the applica-ble energy and carbon taxation rates. On the demandside, the activity level of the KAP aluminium smelteris the main driving force of electricity consumption:the plant is responsible for more than a quarter of thecountry’s electricity consumption.

The scenarios and assumptions were agreed with themain stakeholders in Montenegro (relevant min-istries, transmission system operator, regulator andelectricity experts).

The assessment was carried out using the EuropeanElectricity Market Model (EEMM) developed by the Regional Centre for Energy Policy Research (REKK)and the network model of the Electricity CoordinatingCenter (EKC). The EEMM is a detailed, bottom-up eco-nomic simulation model covering the whole Euro-pean Network of Transmission System Operators forElectricity (ENTSO-E) region, while the EKC networkmodel covers the medium- and high-voltage networkof the South East European (SEE) region.

The following main conclusions could be drawn fromthe scenario modelling:

The stringency of climate policy commitments

has limited impact on wholesale price develop-ment. The wholesale price is dependent on theexpansion of regional generation capacity ratherthan on the ambition level of climate policy. Since,at the regional level, significant capacity expan-sion is foreseen in the coming five years in bothfossil- and renewable-based generation, it willdrive wholesale electricity prices down in thewhole SEE region.

The future generation mix and production levels

are more sensitive to climate policy. While coal-based generation remains relatively constant inthe scenarios, changes in demand (due to the assumed KAP operation level) and RES capacityexpansion result in highly fluctuating import andhydro generation levels. The country could become a significant exporter by 2025, if lower demand is coupled with more intensive hydro capacity expansion.

Montenegro is currently a net importer of electric-

ity and continues to be an importing country inthe REF scenario. However, in the AMB scenariothe country becomes a sizeable exporter of elec-tricity from 2020 onwards. This is due to the lowerdemand (due to the lower utilisation rate of theKAP plant, at 50 percent capacity level) and the sig-nificant increase in hydro-based generation.Higher RES deployment and the future of the KAPplant have a significant impact on the country’strade position, and consequently on its security ofsupply situation.

CO₂ emissions remain stable in the modelled

period. Only the most ambitious policy scenarioresults in a significant reduction by 2030. The carbon intensity of the Montenegrin electricitysystem is higher than the ENTSO-E average. Thisis true not only for the per capita emission level,but also for other carbon intensity indicators —measured in relation to electricity consumptionand production levels. Although Montenegro hasa very high share of hydro generation (around 75 percent of total installed capacity), the highshare of coal generation (around 40 percent) stillmakes the electricity mix highly carbon intensive.Emissions intensity in Montenegro shows a dynamically decreasing trend in all scenarios, butthis improvement is still not sufficient to reach theENTSO-E average values by 2030.

Montenegro could still develop significant capaci-

ties in hydro generation, which could be a veryvaluable asset for the future operation of the elec-tricity system. At present, further deployment isconstrained by security of supply considerations:the country would like to avoid further increasingits dependence on hydro, which is very sensitiveto meteorological conditions (precipitation levelsand patterns). The support levels needed for theassumed RES-E deployment show significant ex-pansion, but would only reach the 2012 levels ofthe Czech Republic, Greece or Portugal by 2020

Page 9: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro8

(EUR 13.4/MWh). Besides, the 2020 value wouldbe the peak, as the required support subsequentlydecreases. The modelling results also show that ifthe country introduces a price tag for carbonemissions (either via a national taxation schemeor the EU Emissions Trading System [ETS]), gov-ernment revenues could roughly finance the re-quired RES-E support budget after 2020.

Generation capacity investments are concentrated

in coal and hydro technologies. Although hydrotechnologies make up the bulk of the investmentcosts due to their relatively expensive constructioncosts, from a generation unit cost perspective(based on levelised cost of electricity [LCOE]) hydrois the cheapest renewable technology.

The security of supply concern is further analysed

by checking the impact of a dry year on the Mon-tenegrin electricity system. This sensitivity assess-ment confirms that Montenegro is sensitive tometeorological conditions: in the short term, se-vere droughts — modelled as the driest of thepast eight years in the region — could drive upprices by EUR 8/MWh, and by EUR 3/MWh in thelong term. In such a year the country would still

rely on imports, although in the AMB scenario —with the highest hydro capacities in operation andwith reduced KAP operation — imports are signif-icantly reduced from the base 40 percent value to8 percent compared to consumption.

The hydro sensitivity assessment also highlights

an important future policy direction for the coun-try. If further cooperation is enhanced within theregion and with EU member states, the countrycould further utilise its hydro potential. In thiscase, the country should be very supportive of astricter EU renewables policy, as this would creategreater demand for its hydro-based generation.

The assessment of network impacts shows that,

in general, the Montenegrin electricity systemwould be sufficiently strong to cope with theplanned RES capacity increase in the scenarios. Ifthe planned network additions are built, no fur-ther contingencies would appear in the system.Net transfer capacity (NTC) would also increase to-wards Serbia, with a minor reduction in NTC to-wards Albania. Network losses would increase inthe scenarios with higher consumption levels andhigher RES-E generation connected to the system.

Executive summary Figure 1 Generation mix, net imports and CO₂ emissions in the three scenarios

Page 10: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 9

Executive summary Figure 2 Tax-based revenues and expenditure on RES-E support

Page 11: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

II. Introduction

Page 12: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 11

The main objective of the SLED project is to help pol-icy makers in Albania, the former Yugoslav Republicof Macedonia, Montenegro and Serbia in setting uprealistic but ambitious decarbonisation pathways fortheir electricity sectors up to 2030. Policy develop-ments should be evidence based, as far as possiblebuilding on quantified modelling results obtainedfrom the possible set of future decarbonisation sce-narios. The SLED project assisted the countries withmodelling, accompanied by a continuous consulta-tion process to enable national policy makers to influ-

ence the scenario development process according totheir needs for their future energy sector and climatestrategy developments. During the modelling exer-cise, policy options related to production levelsand/or the fuel mix for electricity generation — suchas supply-side energy efficiency improvements, theaccelerated retirement of old power plants, increasingshares of renewable energy sources (RES), and elec-tricity demand — were assessed from the perspectiveof CO₂ emissions, generation capacity investmentcosts and renewable support needs.

Page 13: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

III. Methodology

Page 14: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 13

In this section we introduce the framework of thescenarios, including the differentiation dimension,and the two models used in the assessment of the scenarios.

Scenario development frameworkIn order to assess the full range of the decarbonisa-tion potential in the assessed countries, three scenar-ios were constructed for each country in the SLEDproject: Reference (REF); Currently Planned Policies(CPP); and Ambitious (AMB). Scenario assumptionswere related to six dimensions:

carbon value;

energy/excise tax;

environmental standards;

deployment of renewable energy technologies;

deployment of conventional generation tech-

nologies; andelectricity demand (integrating assumptions on

end-use energy efficiency improvement).

The above factors all affect national CO₂ emissionseither via the level of electricity production or by theirimpact on the fuel mix for electricity generation. Asfar as taxation is concerned, two factors can be iden-tified. First, the introduction of the EU Emissions Trad-ing System (ETS) as a consequence of either EUmembership or the transposition of EU law requiredfor members of the Energy Community; and secondsimply the introduction of a national policy instru-ment placing value on carbon emissions, which altersthe cost of the respective generation technologiesand hence the production possibilities. The samelogic applies to the introduction of the minimum taxlevel on energy products required by EU legislation.The electricity supply mix is affected by the introduc-tion of European air pollution regulations: the LargeCombustion Plants (LCP) Directive, for example, mayforce the most polluting coal plants out of operationor limit their operating hours. The development of re-newables and conventional (fossil) generation capac-ities is the outcome of national policy decisions and— in the case of renewables — support levels. Growthin electricity demand triggers higher production fromthe available power plant portfolio or imports.

The REF scenario reflects the business-as-usual devel-opments in the country, meaning that the official en-ergy policy and legislative instruments that were in

place by the closing date of scenario definition (July2015) are included. The CPP scenario reflects those poli-cies that are under consideration and that could havean impact on GHG emissions. The third scenario, AMB,represents the most advanced climate policy stand.

The options included in the scenarios are assessednot only for the individual countries but also in termsof possible synergies from more collaborative actionsamong SEE countries.1 Modelling the various optionslisted above can help to identify the most effective op-tions to reduce CO₂ emissions in the assessed coun-tries. Other impacts, such as those relating to securityof supply and network reliability, are also included inthe analysis.

conDItIons sPEcIFIc to MontEnEgro

The main data and policy inputs for the scenarioswere agreed with relevant stakeholders (Ministry ofEconomy, Ministry of Sustainable Development, trans-mission system operator [TSO], energy regulator andenergy agency) in two rounds. First, in December2014, we agreed with stakeholders on the main as-sumptions of the scenarios (demand growth rates,RES and conventional capacity expansion, cross-bor-der capacities, energy efficiency measures and theKAP aluminium smelter utilisation rates). Based onthese assumptions, the European Electricity MarketModel (EEMM) was run and preliminary results weredelivered. These results were sent to stakeholders andalso presented during a second stakeholder meetingin July 2015. Based on the feedback, the scenarioswere redesigned on the basis of two main factors.First, between the two meetings significant changestook place in Montenegro’s energy strategy (e.g. con-cerning the future utilisation of the KAP aluminiumsmelter). Second, the Ministry of Sustainable Develop-ment expressed an interest in using the modelling re-sults in Montenegro’s intended nationally determinedcontributions (INDC) commitment, thus the scenarioswere redesigned by experts from the ministry in orderto reflect more closely the country’s recent energy pol-icy decisions. The original AMB scenario was also re-designed. It had initially been designed to reflect avery ambitious GHG reduction scenario in order totest maximum GHG emissions reductions and to de-fine the consequences of such a scenario on the RESsupport budget and investment costs. The emphasiswas subsequently changed in order to build a morerealistic scenario that gives input to the INDC planningprocess. (For the final assumptions used in the threescenarios, see Table 5 on page 20.)

Page 15: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro14

ModelsDecarbonisation scenarios for the four assessed coun-tries and the region as a whole were developed withthe state-of-the-art EEMM, used in tandem with the de-tailed technical network model of the Electricity Coor-dinating Center (EKC). The EEMM has been frequentlyapplied in the region in the past in relation to Projectsof Energy Community Interest (PECI) assessment, whilethe network model has been used in many network ex-pansion and upgrade projects in the region.2 TheEEMM is a partial equilibrium model focused on gen-eration capacities, while the EKC network model fo-cuses on the transmission system, in particular on thedevelopment of cross-border capacities. The two mod-els are introduced briefly in this section: more detailedmodel descriptions can be found in the Annex.

The reliability of model results was ensured by work-ing closely together with stakeholders in the region.The EKC network modelling team is from Serbia,which means that the modelling experts have in-depth regional knowledge. In addition to this insiderinvolvement, three project factors gave unique addedvalue to the assessment:

The models were updated with the most recent

data from the beneficiary countries, with the helpof local experts.

Throughout the project, the involvement of stake-

holders — including representatives of relevantministries dealing with climate- and energy-related issues and representatives of TSOs — wasensured by setting up a project “task force”. Theseexperts and policy makers were involved in defin-ing policy-relevant scenarios and in the assessmentof model results already at an early stage of theproject. They also provided up-to-date informationon national energy policies and checked the validityof information and data during two stakeholdermeetings in November 2014 and July 2015.

The dissemination of project results will be en-

sured by means of workshops in all participatingcountries.

The relevant experts and stakeholders in the projectcountries were reached with the help of a local expertconsultancy (EKC from Serbia), as well as the local of-fices of the Regional Environmental Center (REC),which has long-term expertise and a solid network inthe region.

The European Electricity Market Model

The EEEM is a simulation model of the European elec-tricity wholesale market that works in a sytlised man-ner with perfect competition assumptions.

The EEMM covers 36 countries with rich bottom-uprepresentation. In Figure 1, in the countries colouredorange, electricity prices are derived from the demand-supply balance, and in the blue countriesprices are exogenous. The ENTSO-E countries of theEU (Malta and Cyprus are not included in the model)and Balkan countries are modelled in full detail.

In the electricity production sector we have differen-tiated 12 technologies. We assume one interconnec-tor per pair of countries, which means modelling 85transmission lines. The EEMM models the productionside at unit level, which means that at a greater Euro-pean level almost 5,000 units are included in themodel runs. Equilibrium (in prices and quantities) isreached simultaneously in the producer and thetransmission segments. These units are characterisedby various technological factors, allowing the con-struction of the merit order for the particular time period. In each year we have 90 reference hours torepresent the load curve with sufficient detail for eachEuropean country.

There are three types of market participants in themodel: producers, consumers and traders. All ofthem behave in a price-taking manner: they take theprevailing market price as given, and assume thatwhatever action they decide upon has a negligible effect on this price.

Producers are the owners and operators of powerplants. Each plant has a specific marginal cost of pro-duction, which is constant at the unit level. In addi-tion, generation is capacity constrained at the level ofavailable capacity.

The model only takes into account short-term vari-able costs with the following three main components:fuel costs, variable operational expenditure (OPEX),and CO₂ costs (where applicable). As a result, the ap-proach is best viewed as a simulation of short-term(e.g. day-ahead) market competition.

Price-taking producer behaviour implies that when-ever the market price is above the marginal genera-tion cost of a unit, the unit is operated at full availablecapacity. If the price is below the marginal cost, thereis no production at all; and if the marginal cost andthe market price coincide, then the level of production

Page 16: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 15

is determined by the market clearing condition (supply must equal demand).

Consumers are represented in the model in an aggre-gated way by price-sensitive demand curves. In eachdemand period, there is an inverse relationship be-tween the market price and the quantity consumed:the higher the price, the lower the consumption. Thisrelationship is approximated by a downward slopinglinear function.

Finally, traders connect the production and consump-tion sides of a market, export electricity to more expen-sive countries and import it from cheaper ones.Cross-border trade takes place on capacity-constrainedinterconnectors between neighbouring countries. Elec-tricity exchanges always occur from a less expensivecountry to a more expensive one, until one of twothings happens: either prices, net of direct transmis-sion costs or export tariffs, equalise across the twomarkets; or the transmission capacity of the intercon-nector is reached. In the second case, a considerableprice difference may remain between the two markets.

The model calculates the simultaneous equilibriumallocation in all markets with the following properties:

Producers maximise their short-term profits given

the prevailing market prices.

Total domestic consumption is given by the aggre-

gate electricity demand function in each country.

Electricity transactions (exports and imports)

occur between neighbouring countries until mar-ket prices are equalised or transmission capacityis exhausted.

Energy produced and imported is in balance with

energy consumed and exported.

Given our assumptions about demand and supply,market equilibrium always exists and is unique in the model.

The EKC network model

Electric power systems in SEE are modelled with theircomplete transmission networks at 400 kV, 220 kVand 150 kV. The power systems of Albania, the formerYugoslav Republic of Macedonia, Montenegro andSerbia are modelled in addition at the 110 kV voltagelevel. The network equivalent of Turkey (i.e. Europeanpart) and the rest of ENTSO-E Continental Europe

Figure 1 Modelled countries

Page 17: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro16

(modelled over the X-node injections) were used inthe model.

The network model in this assessment provides thefollowing results:

Contingency analyses, which include:

• an assessment of the existing electricity networksituation within Albania, the former Yugoslav Re-public of Macedonia, Montenegro and Serbia,together with the regional context; and

• a definition of the network topologies andregimes for 2015, 2020 and 2025, using realisticscenarios of demand growth, generation expan-sion, transit flows, RES integration and high-volt-age direct current (HVDC) links.

Total and net transfer capacity (TTC/NTC) evalua-

tion between Albania, the former Yugoslav Repub-lic of Macedonia, Montenegro and Serbia in alldirections, for all topology scenarios.An assessment of transmission grid losses, with

and without a level of energy production from RES.

stEADy-stAtE AnD contIngEncy AnALysEs

For the defined scenarios, steady-state load flows arecalculated and contingency (n-1) analyses performed.Security criteria are based on the loadings of lines andvoltage profile, and will be checked for each scenarioanalysed.

Load-flow assessment is a basic step for NTC evalua-tion, and it comprises the following analyses:

steady-state AC load-flow analysis;

a security (n-1) assessment, where the tripping of

lines is simulated. This means that one line is con-sidered out of service, while load flow is calculatedand the security of the system assessed (circuitoverloads and voltage violations); and

a voltage profile analysis.

In the analysis of voltage profiles, voltage limits areaccording to the respective national grid codes.

EVALuAtIon oF nEt trAnsFEr cAPAcIty

Total and net transfer capacity (TTC/NTC) were evalu-ated between Albania, the former Yugoslav Republicof Macedonia, Montenegro and Serbia, as well as be-tween these countries and their neighbours, in all directions, for all topology scenarios, with referenceto each target year and regime, and a final assess-

ment was made of the TTC/NTC additional values asa result of the new interconnections and the strength-ening of the major internal energy transit routes.

General definitions of transfer capacities (TTC andNTC) and the procedures for their assessment weregiven by ENTSO-E, as well as by the practice and experience of regional SEE TSO working groups.

The methodology used in performing this study wasbased on the prerequisites outlined below.

trAnsMIssIon grID LossEs

The assessment of electricity losses is based on lossesover the equivalent time duration in winter peak andsummer peak periods. This approach takes into ac-count that the effect on losses may be different inthese two regimes, as a result of which losses onyearly level can be determined more accurately.

Model assumptionsIn this section we introduce those assumptions thatremain constant across the various scenarios of allthe assessed countries and the regional assessmentas well.

Cross-border network capacities

Even though countries in the SEE region are well con-nected with their neighbours, further capacity exten-sions are envisaged in the future. The model uses theNTC values of ENTSO-E to reflect the trading possibil-ities between countries. Tables 1 and 2 show the pres-ent NTC values in the region, including neighbouringcountries, and the planned new connections in themodelling timeframe.

The Montenegro–Italy 1,000 MW submarine cable isplanned to start operation in 2018. Construction hasalready started and is proceeding according to the in-vestment plan. The other submarine cable connectingItaly with Albania is very uncertain and might not berealised as planned, or might even be cancelled. Themodelling considers the “approved” and “under con-struction” categories of ENTSO-E in all three scenarios.

Current generation capacities

Table 3 provides information on electricity generationcapacities for the base year, 2014.

Page 18: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 17

Fossil fuel prices

Table 4 shows the fossil fuel prices applied in themodelling for the period 2015–2030.

European Union Emissions Trading System price

Concerning the carbon price assumptions, we fol-lowed the carbon value path of the latest impact assessment of the EU (GHG40EE scenario3) and as-sumed an ETS carbon price of EUR 22/tCO₂ for Europeby 2030. The ETS price goes linearly from its 2014value of EUR 6/t to EUR 22/t by 2030 in all scenarios.

European Union minimum tax levels forenergy products

Excise duty is differentiated according to the fuel used(coal, natural gas and heavy fuel oil [HFO]). The mini-mum excise duty level applied is equal to the 2014level applicable by EU law:

EUR 0.3/GJ for natural gas;

EUR 0.15/GJ for coal; and

EUR 0.38/GJ for HFO.

Table 1 Present net transfer capacity values in the region (MW)

Origin and destination country NTC value

From To O➞D D➞O

AL MK 0 0

BA RS 488 403

BA ME 483 440

GR MK 329 151

GR AL 250 250

HR RS 507 429

HU RS 689 758

ME AL 400 400

MK BG 96 215

RO RS 570 347

RS ME 540 583

RS MK 491 253

RS AL 223 223

RS BG 162 250

Source: ENTSO-E

Page 19: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro18

notEs

See the regional assessment.1

In the network assessment of the 400 kV line between Montenegro, Serbia and Bosnia and Herzegovina, for example.2

Commission Staff Working Document, “Impact Assessment: A policy framework for climate and energy in the period from 2020 up to 2030”.3

SWD(2014) 15 final.

Table 2 Planned interconnectors and their investment status (MW)

Country 1 Country 2 Year of commissioning Investment status O➞D D➞O

RS RO 2017 Approved 800 800

BA ME 2023 Planned 600 600

IT AL 2020 Planned 500 500

RS MK 2015 Under construction 400 1,000

MK AL 2019 Approved 600 600

AL RS 2016 Under construction 500 500

IT ME 2018 Under construction 1,000 1,000

RS BA 2022 Planned 600 600

RS ME 2022 Planned 600 600

Source: ENTSO-E

Table 3 Electricity generation capacities, 2014

Coal andlignite Natural gas HFO/LFO Hydro Wind Biomass PV Total

AL 0 0 0 1,801 0 5 2 1,807

ME 210 0 0 661 0 7 3 881

MK 824 290 210 644 37 0 15 2,020

RS 4,672 0 0 2,357 331 1 7 7,368

Source: REKK and PLATTS database

Table 4 Fuel prices, 2015–2030

Coal price (EUR/GJ) Lignite price (EUR/GJ) West European naturalgas price (EUR/GJ)

East European natural gas price (EUR/GJ)

2015 2.0 1.2 5.5 8.3

2020 2.2 1.3 5.9 8.0

2025 2.2 1.3 6.0 8.1

2030 2.2 1.3 6.2 8.3

Source: IEA and EIA projections

Page 20: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

IV. Scenario assumptions

Page 21: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro20

Table 5 summarises the scenario assumptionsgrouped under taxation, supply-side measures anddemand-side measures.

These assumptions are based on the existing energystrategy documents of Montenegro and the out-comes of the two stakeholder meetings that were

Table 5 Main scenario assumptions for Montenegro

Scenario assumptions

Reference GHG scenario(REF)

Currently Planned PoliciesGHG scenario (CPP)

Ambitious GHG policyscenario (AMB)

Taxation

Introduction of EU ETS ETS to be introduced in 2025 CO₂ cost in 2020 is 40% ofthe ETS price; from 2025 ETS

is introduced ETS to be introduced in 2020

Introduction year ofminimum excise duty Year of introduction: 2020 Year of introduction: 2020 Year of introduction: 2018

Electricity supply

Enforcement ofenvironmental standards

(LCP Directive)

Due to the requirements ofthe LCP Directive, Pljevlja I

closes in 2023.

Due to the requirements ofthe LCP Directive, Pljevlja I

closes in 2023.

Due to the requirements ofthe LCP Directive, Pljevlja I

closes in 2023.

RES-E deployment

NREAPs: 826 MW hydro; 151 MW wind; 10 MW PV;and 29 MW biomass by2020. By 2030: 826MW

hydro; 190 MW wind; 32 PV;and 39 MW biomass.

NREAPs: 826 MW hydro; 151 MW wind; 10 MW PV;and 29 MW biomass by2020. By 2030: 826MW

hydro; 190 MW wind; 32 PV;and 39 MW biomass.

NREAPs: 826 MW hydro; 151 MW wind; 19 MW PV;and 29 MW biomass by2020. By 2030: 1,267 MWhydro; 229 MW wind; 32 PV;and 64 MW biomass.

Conventional capacitydevelopments

Pljevlja II comes online in2023 (254 MW) and Pljevlja Icloses in 2023. Maoce TPPwill not be built. For the LCPDirective: Pljeva I will operateuntil 2023 (20,000 hoursbetween 2018 and 2023).

Pljevlja II comes online in2023 (254 MW) and Pljevlja Icloses in 2023. Maoce TPPwill not be built. For the LCPDirective: Pljeva I will operateuntil 2023 (20,000 hoursbetween 2018 and 2023).

Pljevlja II comes online in2023 (254 MW) and Pljevlja Icloses in 2023. Maoce TPPwill not be built. For the LCPDirective: Pljeva I will operateuntil 2023 (20,000 hoursbetween 2018 and 2023).10% biomass utilisation rateis assumed for Plejva II.

Electricity demand Electricity demand

According to the May 2014Strategy (KAP operates withtwo lines at 100% capacityfrom 2019). Means 100%total presently installedcapacity (A and B line).

50% of the total installedcapacity, according to theagreement at the July 2015stakeholder meeting. Onlyone line operating at 100%.

50% of the total installedcapacity, according to theagreement at the July 2015stakeholder meeting. Onlyone line operating at 100%.

Page 22: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 21

held in Podgorica in December 2014 and July 2015.The energy policy documents that were used are:

Energy Efficiency Action Plan of Montenegro for

2013–2015, Ministry of Economy, November 2013

National Renewable Energy Action Plan (NREAP)

of Montenegro, Ministry of Economy, 2014

Montenegrin Energy Strategy up to 2030, Godine

(Bijela Knjiga), 2014

Update/Upgrade of the Energy Development

Strategy of Montenegro by 2030 (Green Book and

draft White Book), Ministry of Economy, 2012

Introduction of the European UnionEmissions Trading SystemWe used different assumptions with respect to Mon-tenegro joining the EU ETS. In the REF scenario, Mon-tenegro joins the ETS in 2025, while in the CPPscenario the power sector already faces a carbonvalue equal to 40 percent of the EU ETS price in 2020.In the AMB scenario, the Montenegrin power sectorjoins the ETS already in 2020. “Joining the ETS” doesnot necessarily imply EU membership: we only as-sume that national policy makers will apply some in-struments with similar effects on the electricitysector as the EU ETS (e.g. by a voluntary or legal ob-ligation, or through a national or Energy Communitycommitment).

Introduction of minimum excise duty on energy productsConcerning other taxes in the energy sector, we usedthe assumption that the country introduces the min-imum level of excise duties in 2020 in the REF and CPPscenarios, while in the AMB scenario it is already introduced in 2018.

Environmental standards enforcementWe assume that the country fulfils the requirementsof the EU LCP Directive, which means that the Pljevlja I coal-fired plant will be closed in 2023 at thelatest and can operate for only 20,000 hours between2018 and 2023.

Deployment of renewable energy sources for electricityMontenegro finalised its NREAP for the Energy Com-munity Secretariat in December 2014. This documentis the basis for our modelling and provides plannedcapacity values up to 2020. Figures beyond 2020 arebased on the Energy Strategy Development docu-ment of 2012, which contains forecasts up to 2030(see Table 6).

Up until 2020, all scenarios use the NREAP numbers.From 2020 onwards in the REF and CPP scenarios,hydro generation capacity is kept constant. The rea-son for this limiting assumption is that the growth inhydro capacity in the 2015–2020 period is alreadyquite strong, reaching a significant increase by 2020.In the AMB scenario, we allow further growth, reach-ing the level of hydro capacities according to the2012 Green Book on Energy Strategy Development,meaning doubling the present level of hydro capac-ities by 2030. Other renewable capacities in the REFand CPP scenarios are according to the Green Bookfigures for the years between 2020 and 2030. Theyare relatively small, especially if we also assume thatin the meantime the country probably joins the EU.For this reason, in the AMB scenario the growth ratesof non-hydro renewable capacities are further in-creased, in order to analyse the impact of strongerRES-E deployment in the sector. These scenarios as-sume normal utilisation conditions for weather-dependent technologies (solar, wind), meaning average working hours and efficiency. Concerninghydro generation in these scenarios, average hydro-logical conditions are assumed. This assumption willbe relaxed in the sensitivity assessment, where a lowprecipitation pattern is also assessed. The EEMMtreats RES-E capacities in a “must run” operationmode in order to reflect the priority dispatch of renewable technologies.

Conventional power plantsMontenegro currently has only one fossil fuel plant,Pljevlja I, with a capacity of 210 MW, fuelled with domestic coal. The plant uses old condensation tech-nology that does not meet the requirements of theEU LCP Directive. Consequently, the plant is sched-uled to be closed down in 2023 and is permitted onlya limited number of operating hours (20,000 hours

Page 23: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro22

Table 6 Capacity deployment of renewable energy sources for electricity in the scenarios (MW)

REF scenario 2015 2016 2017 2018 2019 2020 2025 2030

Hydro* 661 744 753 821 826 826 826 826

Pumpedstorage 0 0 0 0 0 0 0 0

Geothermal 0 0 0 0 0 0 0 0

Solar 3 6 7 8 9 10 22 32

Wind 0 118 126 126 151 151 172 190

Biomass 7 9 14 18 19 29 33 39

CPP scenario 2015 2016 2017 2018 2019 2020 2025 2030

Hydro* 661 744 753 821 826 826 826 826

Pumpedstorage 0 0 0 0 0 0 0 0

Geothermal 0 0 0 0 0 0 0 0

Solar 3 6 7 8 9 10 22 32

Wind 0 118 126 126 151 151 172 190

Biomass 7 9 14 18 19 29 33 39

AMBscenario 2015 2016 2017 2018 2019 2020 2025 2030

Hydro* 661 744 753 821 826 826 1 047 1 267

Pumpedstorage 0 0 0 0 0 0 0 0

Geothermal 0 0 0 0 0 0 0 0

Solar 3 6 7 8 9 10 22 32

Wind 0 118 126 126 151 151 172 190

Biomass 7 9 14 18 19 29 57 64

*Excluding pumped storage

Page 24: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 23

between 2018 and 2023). According to the nationalenergy policy, the power plant will be replaced by anew block with a capacity of 254 MW (Pljevlja II). Theselected developer and constructor is Skoda (CZ) andthe government is in advanced negotiations for theconstruction of the plant. Although the latest officialdate for the plant to start operations is 2020, this isnot realistic, since licensing, building and testing sucha coal-fired plant would require a longer lead time. Inagreement with stakeholders, the earliest assumedstarting date is 2023, and this date is used in themodel. The earlier Energy Strategy of Montenegro(2012) also counted on building an additional coal-fired plant (TPP Maoce), although its construction isno longer envisaged. The construction of Pljevlja II isforeseen in all scenarios. In the AMB scenario, it is assumed that Pljevlja II uses 10 percent biomass (co-firing).

Electricity demandElectricity consumption usually closely follows a coun-try’s GDP development. We did not prepare our ownforecast based on GDP assumptions, but used the lat-est official energy forecast (Energy Strategy of 2014)for the Montenegrin power system (Table 7).

The main difference between the scenarios is the as-sumed utilisation rate of the KAP aluminium smelter.If operated at 100 percent of its installed capacity, theKAP plant is responsible for more than one-third ofnational electricity consumption. However, there arebig uncertainties concerning the future operation ofthe smelter. It consists of two producing lines (lines Aand B) but currently only one line operates, at a loadlevel of 84 MW. This limit is set in the discounted elec-tricity price contract between the company and thenational electricity provider. According to the agree-ment reached at the second stakeholder meeting, a100 percent utilisation rate is assumed in the REF sce-nario, while in the other two scenarios the operationof one producing line is assumed. The values in Table 7 illustrate the significant role that the KAP plantplays in the electricity market of Montenegro. As theKAP plant’s core technology is quite old, the electricityprice for the company and global aluminium marketdevelopments could have a significant impact on thefuture operation of the company.

Concerning energy efficiency improvements, we didnot differentiate between the scenarios. We used im-provements of 4 and 7 percent electricity savings com-pared to the “without measures” energy efficiencypath, calculated on the basis of the energy strategydocument of Montenegro (Green Book 2012). This as-sumption is already included in the figures above.

Table 7 Gross electricity consumption in Montenegro (GWh)

GWh 2015 2016 2017 2018 2019 2020 2025 2030

REF 3,518 3,629 3,743 3,861 5,173 5,298 5,838 6,449

CPP 3,518 3,629 3,743 3,861 3,925 4,050 4,590 5,201

AMB 3,518 3,629 3,743 3,861 3,925 4,050 4,590 5,201

Page 25: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

V. Modelling results

Page 26: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 25

In this section we discuss the results of the modellingrelated to wholesale price development, the electric-ity generation mix, CO₂ emissions, renewable sup-port and investment needs for the generationcapacities included in the respective scenarios.

Price developmentOne of the most important indicators of the function-ing of an electricity market is the development of awholesale price. Sudden and significant price changesare a sign of the malfunctioning of the electricity mar-ket, as they generally indicate shortages of certaingeneration capacities or problems with cross-bordertrade. As hydro capacities are an important source ofelectricity generation in Montenegro, changes in pre-cipitation patterns can also change the price patternin the electricity sector. This issue is addressed in Section VI (Sensitivity assessment).

Figure 2 shows the base-load price development inMontenegro in the various scenarios. The yearly base-

load price development is shown as the calculated av-erage of the modelled base-load hours in the year. Inthis way, it is possible to smooth out the cyclical behaviour of electricity prices over a year in order to illustrate the main trends.

One of the most important things shown by the figureis the minor differences between the scenarios. Whilethere is a big fluctuation in terms of price betweenthe years, there is no significant variation between thescenarios. This shows that, from the point of view ofwholesale price, more ambitious GHG policies arefeasible in the Montenegrin electricity system, thusthe power sector (together with import possibilities)would be able to cope with the assumed GHG policyinstruments without any significant price increase.The impacts on electricity imports and the RES sup-port budget will be analysed later. What can be ob-served as a general trend in the projection is a fallingbase-load price level in the next five years, followedby a slightly increasing trend up to 2030. The reasonfor the significant price drop in the near future is thedynamically growing capacity pool in the region,which is analysed below under “Regional outlook”.

Figure 2 Base-load price evolution in the various scenarios (EUR/MWh)

Page 27: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro26

Another interesting trend is the reduction in peak-load prices, which are getting closer to the base-loadprice by 2030. Montenegro’s increasing connectivityand more available capacities make shortages on thesupply side less frequent, which — in turn — resultsin the convergence of base and peak prices, as illus-trated in Figure 3. The same conclusion holds for thepeak-load prices as for the base-load prices: the sce-narios do not show any significant price differencesin the wholesale market prices.

Regional outlookThe plummeting price trend in the first five years requires a more detailed explanation. The maindriving force behind this development is the dy-namic capacity expansion in the region.4 As thecountry is well connected with its neighbours, anyincrease in generation capacities in neighbouringcountries will also increase supply in Montenegro,thus reducing prices in the whole region. As shownin Figures 4 and 5, there is a significant peak in the

construction of new power plants in the region in2015–2020.

As Figures 4 and 5 illustrate, most of the new fossil-based generation is due to be built in the coming fiveyears, meaning a significant and quite rapid increaseon the generation side. This increase in generation iscomplemented by an even more sizeable increase inrenewable capacities, mainly wind and hydro. Allthese new plants represent a significant pressure onthe supply side, and, if realised, could lead to signifi-cant price reductions in the coming years. As many ofthese plants are under construction or have a final in-vestment decision (FID), they will probably be built,even in an environment of falling electricity prices.Under these investment conditions, project develop-ers are trying to finalise their projects as soon as pos-sible, as new entrants will deter other investors fromentering the market. However, this might lead to a sit-uation in which all new entrants lose money, as thefalling price trend would undermine the long-termprofitability of the fossil fuel–based plants (mainlycoal-based generation), especially if accompanied byan increasing carbon price trend.

Figure 3 Peak-load price evolution in the various scenarios (EUR/MWh)

Page 28: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 27

Figure 4 Planned new fossil fuel–based capacities in South Eastern Europe, 2015–2030

Figure 5 Planned new renewable-based capacities in South Eastern Europe, 2015–2030

Source: EEMM database, Platts

Source: EEMM database, Platts

Page 29: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro28

Generation mixWhile we can observe less-pronounced changes in thewholesale electricity prices, the various policies haveprofound impacts on the electricity generation mix, onthe export-import position of the country, and thus onCO₂ emissions. Figure 6 summarises the above-men-tioned impacts of the three assessed scenarios.

In terms of the generation mix in the scenarios, themost important changes can be observed in hydro-based generation: the AMB scenario assumes moredynamic hydro capacity investments. Wind genera-tion contributes significantly to the future generationmix in Montenegro in the REF and CPP scenarios,while in the AMB scenario biomass is also a sizeablecontributor. Coal-based generation also increasesdue to the higher capacity of the new Pljevlja II plantcompared to the existing plant, which will be closedby 2023 as it is not able to fulfil the requirements ofthe LCP Directive. The utilisation rate of the new coalplant is around 75 percent by 2030, which creates un-certainty about its ability to break even in the longterm. Emissions of CO₂ are around 1,700 Mt in most

scenarios, dropping to 1,540 Mt in the AMB scenarioby 2030. This is due to higher RES penetration, to thelower utilisation rate of the coal-fired plant, and to the10 percent biomass co-firing option applied in thenew Pljevlja II coal-fired plant.

CO₂ impactsIn this sub-section we assess the impacts of the various scenarios on CO₂ emissions using four indicators:

CO₂ per capita;

CO₂ per GWh production;

CO₂ per GWh consumption; and

fiscal impact of the introduced taxes

We look at the first three indicators in relation to theENTSO-E average in order to measure the country’srelative performance.

Despite the very high level of available hydro capacity,Montenegro has higher CO₂ emissions per capita

Figure 6 Generation mix, net imports and CO₂ emissions in the three scenarios

Page 30: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 29

than the ENTSO-E average (Figure 7). This is not sosurprising, considering the fact that the rest of thegenerated electricity comes from the coal-firedPljevlja I plant. Pljevlja I represents around 40 percentof total generation, while in Europe less than 25 per-cent of total electricity generation is based on solidfuels (coal and lignite). In addition, per capita emis-sions in Montenegro remain high, with the exceptionof the AMB scenario where significant reductions areforeseen due to higher RES deployment, the lowerutilisation of the KAP smelter, and a higher carbonprice. However, in the AMB scenario, CO₂ emissionsin the sector are still higher than the ENTSO-E aver-age. The drop in emissions in the scenario is due tothe fact that, with the introduction of carbon taxation,coal-based generation becomes less competitive,thus its production is reduced. It should be empha-sised that this effect is more pronounced in the indi-vidual case of Montenegro than in the regionalassessment, where all countries introduce carbontaxation at the same time and at the same ratio.

The CO₂ intensity of electricity consumption indicator(Figure 8) shows a more favourable picture. Although

in 2015 the country is still well above the ENTSO-E av-erage, in the 2020–2030 period the reduction issteeper than in the ENTSO-E region, thus by 2030, inmany scenarios, CO₂ emissions come close to theENTSO-E average. The fact that the REF scenario re-sults in the lowest emissions by 2030 is due to thehigher consumption level being satisfied almost ex-clusively by imports. The regional impact of these im-ports is assessed in the regional study.

The production-based indicator (Figure 9) shows asimilar trend to the consumption-based indicator:CO₂ intensity that is higher than the ENTSO-E aver-age, but with a rapidly decreasing trend. In this casethe scenarios show a more consolidated picture: theAMB scenario results in the lowest value, very closeto the ENTSO-E average, while the REF values aremuch higher. Again, this reduction is mainly due tothe unilateral carbon value path assumed and thehigher penetration rates of renewables, mainly hydro.

Excise and carbon taxes mean government revenuesfrom the electricity sector. As Figure 10 shows, carbonrevenues are a significantly more important source

Figure 7 CO₂ emission levels per capita

Page 31: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro30

than excise taxes on energy products. Due to thestepwise introduction of the ETS carbon price, the rev-enue streams show an increasing trend, reachingaround EUR 35 to 40 million by 2030. This revenuecould be used to finance important segments of theenergy sector, for example renewables or energy ef-ficiency policies. The revenue level would be sufficientto compensate the RES support budget in the REF andCPP scenarios, and would be slightly below in theAMB case. Logically, the AMB scenario shows the low-est levels of carbon revenue due to the lower emis-sions, although all scenarios show a reliable level ofrevenue flow for the central budget.

Net import positionThe most significant variation between the scenariosappears in relation to import levels. The country iscurrently close to self-sufficiency: domestic demandis mainly covered by domestic production. In this con-text, the future scenarios are markedly different.While the REF scenario shows a steeply increasing im-

port balance, in the AMB scenario the opposite effecttakes place: the country becomes an exporter of elec-tricity (Figure 11).

Figure 11 illustrates an important co-benefit of higherRES deployment in Montenegro: import dependencydecreases significantly. Compared to net imports inthe range of 25 percent in the REF scenario, in theAMB scenario Montenegro would export over 20 per-cent of its generated electricity. There are two maindrivers behind this development. The first is the lowerdemand due to the lower utilisation rate of the KAPaluminium smelter. Secondly, greater RES-E capacitywill enable higher production rates and higher ex-ports to neighbouring countries, including Italy, whichwill be connected to the region by the 1,000 MW sub-marine cable between Italy and Montenegro.

These results will be further analysed in Section VI(Sensitivity assessment), where the assumption regard-ing the average hydro utilisation rate will be relaxedand the production pattern checked against the newassumption regarding hydro generation availability.

Figure 8 CO₂ intensity of electricity consumption (tCO₂/GWh)

Page 32: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 31

Investment costsThe foregoing sections present the multiple benefitsthat appear in the AMB scenario characterised bystronger GHG reduction policy instruments. However,it is important to assess the financial consequencesof more stringent climate policies targeting the elec-tricity sector. This will be done by considering twotypes of costs: the investment cost for generation capacities; and the RES-E support budget.

The investment costs required to build up the new ca-pacities in the electricity sector are shown in Table 8.

The sources of information concerning unit invest-ment costs (shown in the second column, EUR/kW)are a 2013 publication by the Fraunhofer research or-ganisation5; and the Serbian Energy Strategy, whichgives region-adjusted values for the investmentcosts. While most of the renewable and natural gas–based estimates are in a similar range, estimates inthe case of hydro and coal generation investmentcosts deviate significantly. We use benchmark invest-

ment cost values, as national quotes generally under-estimate costs.6

As Table 8 shows, the AMB scenario doubles the cu-mulated investment cost compared to the REF or CPPscenarios, due to the higher RES capacity deployment(mainly hydro generation). While the unit investmentcosts are higher for hydro than for solar or wind tech-nologies, the levelised cost of electricity (LCOE) in thecase of hydro technology is lower than for wind orsolar (see later). In addition, its higher utilisationrates and regulatability makes hydro more attractivein the region. On the other hand, hydro generationraises greater environmental concerns, as the con-struction of new dams and reservoirs is generallymore difficult now, with many new environmentalregulations in place, and many of the newly plannedhydro plants are located in environmentally sensitiveareas. It is important to emphasise that the Pljevlja IIplant and the new hydro power plants are responsi-ble for most of the investment costs (around 80 per-cent), while the contribution of wind, biomass and PVis limited in the scenarios.

Figure 9 CO₂ intensity of electricity production (tCO₂/GWh)

Page 33: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro32

Support budget for renewable energysources for electricityThe next assessed cost element is the RES supportbudget, which indicates the overall financial burdenof RES-E deployment. We calculate with a benchmarksupport need, as present national support levelsmight not reflect the LCOE of the technologies.

The support need for 1 MWh of RES-E is calculated bytaking the LCOE of the various generation technolo-gies, which reflects the full average cost of renewablegeneration, including not only the marginal operatingcosts but also the financial returns needed to coverthe investments.7 To make RES production breakeven, the difference between the LCOE value and themarket price (P) must be given to producers for everyproduced MWh of renewable electricity, which is thesupport need for RES-E production. Base-load andpeak-load prices are used from EEMM runs, makingit possible to calculate the support need for eachMWh of RES-E produced. We assume this support

need is independent of the type of support applied(feed-in tariff [FIT] or feed-in premium). If this supportneed is multiplied by the projected quantity of gener-ated RES-E, we arrive at the support budget. The cal-culation is shown in the following equation:

Support budget = (LCOEt-P)*generated electricity

LCOEt: levelised cost of electricity generation of•technology t ~ average cost of electricity produc-tion

P: modelled base-load electricity price (except•PV, where peak-load electricity prices are takeninto account)

We use a differentiated LCOE for all RES-E technolo-gies, based on data from the literature. One of themost recent reliable calculations (Ecofys, 20148) givesthe following benchmark LCOE data, which were usedin this study:

EUR 55/MWh for hydro;

EUR 90/MWh for wind;

EUR 110/MWh for biomass;

Figure 10 Revenues from the Emissions Trading System and excise tax

Page 34: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 33

EUR 105/MWh for PV; and

EUR 80/MWh for geothermal.

Present FIT support in the country for new hydro ca-pacities is set at between EUR 50 and EUR 100/MWhfor capacities up to 15 GWh production; for PV it is setat EUR 150/MWh; for wind at EUR 96/MWh; and forbiomass at EUR 120/MWh. The benchmark LCOE val-ues show that the present level of support in Mon-tenegro will also be sufficient to cover all types of RESin the future, so there is no pressure to further in-crease support for the technologies.

If the RES-E support budget is divided by the totalelectricity consumption — assuming that all electricityconsumers have to pay for the RES electricity support— we can also calculate the average RES support feethat each end user has to pay according to their con-sumption. These values — the total annual RES-E sup-port budget and the average RES support fee — areshown in Figures 12 and 13.

Figure 12 shows the steeply increasing supportbudget between 2015 and 2020 (mainly due to whole-sale price fluctuations), but also a decreasing budget

after 2020, despite the continuously growing RES-Ecapacities. There is a peak in the support budget inaround 2020, after which financing becomes lesscostly in overall terms. In the REF and CPP scenarios,the reduction in the budget is significant, while in theAMB scenario, with higher RES-E penetration (mainlycomprising hydro capacities), the decrease is observ-able but less pronounced.

Figure 13 illustrates what this support means for endconsumers in terms of the price increase they willface due to the higher deployment of RES-E.

The average RES-E charge on consumed electricity fol-lows a similar trend as in the case of the overall RES-Ebudget. The extra charge is the highest in the CPP sce-nario in 2020, reaching a peak of EUR 15.5/MWh (orEUR 0.0155/kWh). This charge is significant: by 2020the support level in the REF and CPP scenarios reachesthe level at which many European member statesstood in 2012. According to a 2015 report by the Coun-cil of European Energy Regulators (CEER) on EU renew-able support schemes, EU member states supportedRES-E with an average of EUR 13.68/MWh in 2012.9

Figure 11 Net import position changes in Montenegro in the three scenarios

Page 35: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro34

Figure 12 Annual renewable energy sources for electricity support budget (EUR million)

Table 8 Cumulated investment costs in 2015–2030 in the three scenarios

Investmentcost (EUR/kW)

New capacity (MW) Investment cost (EUR million)

REF CPP AMB REF CPP AMB*

Natural gas 1,000 0 0 0 0 0 0

Coal 2,000 254 254 229 508 508 457

Hydro 2,500 166 166 607 414 414 1,516

Geothermal 4,000 0 0 0 0 0 0

Solar 1,100 29 29 29 32 32 32

Wind 1,000 190 190 190 190 190 190

Biomass 3,000 32 32 57 96 96 172

Total – 670 670 1,111 1,239 1,239 2,367

*Due to the 10 percent biomass co-firing in Pljevlja II, additional costs are accounted for the biomass capacities.

Page 36: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 35

Figure 13 Average support for renewable energy sources for electricity from end consumers (EUR/MWh)

notEs1 “The region” includes Albania (AL), Bosnia and Herzegovina (BA), Croatia (HR), Bulgaria (BG), Greece (GR), Hungary (HU), the former Yugoslav

Republic of Macedonia (MK), Montenegro (ME), Romania (RO) and Serbia (RS).

2 Levelized Cost of Electricity Renewable Energy Technologies, Fraunhofer Institute for Solar Energy Systems ISE, November 2013

3 A recent example from the region is the Sostanj coal-fired TPP in Slovenia. The initial investment cost estimate was EUR 700 million for agross 600 MW coal plant (net output 545 MW), and the final investment cost was EUR 1,400 million, equal to EUR 2,500/kW. Source: BalkanEnergy News, June 2015.

4 The most common way to calculate LCOE is:

where I = investment costs; M = maintenance costs; F = fuel costs; E = electricity generated in time t; r = discount rate; and t = time pe-riod.

5 Subsidies and costs of EU energy, Ecofys, November 2014, Final report DESNL14583

6 Status Review of Renewable and Energy Efficiency Support Schemes in Europe in 2012 and 2013, Council of European Energy Regulators,

Only in the CPP and AMB scenarios in 2020 does theaverage support exceed the 2012 EU average. Thus,despite the significant increase, the financial burdenof projected support in 2020 is comparable to the level

of support in the Czech Republic, Greece or Portugalin 2012. The projected average charge also peaks in2020 and subsequently follows a declining trend.

Page 37: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

VI. Sensitivity assessment

Page 38: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 37

Hydropower plays an important role in the region, ashigh levels of hydro capacity exist in almost all the as-sessed countries. Albania leads these countries, rely-ing almost exclusively on hydropower, although theshare of hydro generation capacity is also high inMontenegro (currently over 75 percent). This poses achallenge, as in dry years electricity imports can riserapidly. On the other hand, as this raises security ofsupply concerns for the country, this aspect must beassessed in greater detail. It should be emphasisedthat this is another reason why most SEE countriesare cautious about further increasing their share ofhydro capacities, as to do so would be to furtherdeepen their exposure to meteorological conditions(i.e. to the quantity and seasonality of precipitation).

In order to investigate this issue, a sensitivity assess-ment was carried out that assumed lower precipita-tion levels than in the previous three scenarios. In theREF, CPP and AMB scenarios, hydro utilisation ratesare modelled on the average level over the past eightyears, while in the sensitivity runs we checked thesescenarios using the lowest utilisation rate during thepast eight years, mimicking the situation in a dry year.

As droughts usually occur in the same years through-out the region, we modelled the sensitivity runs ac-cordingly: all neighbouring countries experience alower level of precipitation. This is an important as-sumption, since droughts affect these countries in asimilar way and drive import and export prices up-wards in a similar pattern.

We focus on two aspects in this sensitivity assess-ment: the substitution possibilities within the countryto compensate for the loss in hydro generation; andthe impacts on export-import positions. Figure 14 illustrates the substitution effects in the case of lowerthan usual hydro generation.

As shown in Figure 14, the decrease in hydro genera-tion is mainly substituted by imports in most yearsand in most scenarios. The increase in coal-basedgeneration is only significant in one case — in 2020 inthe AMB scenario — while in all other cases substitu-tion by coal-based generation is less than 3 percent.This shows that the coal-based Pljevlja plant is highlyutilised, but if demand is at its peak, imports are required to meet the extra demand. Security of sup-

Figure 14 Change in the electricity mix in the case of low hydro availability

Page 39: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro38

ply concerns are supported by this result, as importsgrow significantly. On the other hand, cross-bordercapacities are sufficient to provide the requiredpower. The impact is stronger in the AMB scenariodue to the higher share of hydro generation.

Figure 14 also shows the impacts on CO₂ emissions.When hydro generation is substituted by coal, thereis also an increase in emissions. However, imports arenot accounted in the national GHG emissions of Mon-tenegro, while CO₂ emissions would definitely growin the neighbouring countries (carbon leakage).

Figure 15 shows the impact on the export/import position of Montenegro in greater detail.

Lower than usual levels of rainfall have a significantimpact on the country’s import position. The net im-port position decreases by around 750 GWh, oraround 15 percent of Montenegro’s gross consump-tion. While in the AMB scenario the country would be-come a significant exporter in a “usual” year, theseexports would be cancelled out by drought.

The overall conclusion to be drawn from the sensitiv-ity assessment is that security of supply concerns dueto exposure to higher levels of hydro generation arewell founded. However, this statement only holds iftaken purely from a national point of view. If a moreregional view is taken (see the regional assessmentfor more detail), we can say that, due to the high levelof interconnectedness between SEE countries, thereis no shortage of capacity to satisfy overall regionaldemand, even in a dry year, if the planned capacitiesincluded in the scenarios are built. The market oper-ating model of the Nordic countries could also servefor this region. Under favourable hydrological condi-tions, the region could sell hydro-based electricity toits neighbours, while in dry years imports would in-crease. This market model would also enable thebuilding of more hydro capacities in the region with-out imposing extra costs on consumers, and wouldalso reduce security of supply concerns. The high(and increasing) interconnection rates in the regionwould allow for such cooperation, and countrieswould be in a win-win situation. In this case, the

Figure 15 Changes in the net import position of Montenegro

Page 40: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 39

region would not be disadvantaged by a more strin-gent European climate and renewables policy, as itwould create greater demand for their expandinghydro capacities.

Figure 16 illustrates the wholesale price changes inthe scenario runs.

Although in 2015 the price impact is significant,mainly due to a constrained supply side, after 2020the impact is limited to around EUR 3/MWh in all sce-narios. This latter development is probably the resultof capacity developments in the region, which are ex-plored in Section V under “Regional outlook”.

Figure 16 Base-load price changes in Montenegro (EUR/MWh)

Page 41: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

VII. Network impacts

Page 42: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 41

The electricity transmission system in SEE is relativelywell developed for the current level of power ex-changes in the region. However, the exchange possi-bilities in the region are limited by bottlenecks in bothinternal networks and interconnections. Improvingthe balance between energy supply and demand iscrucial in order to boost and sustain economic devel-opment in SEE. This also means that transmission sys-tem operators should be prepared to support energytrading between their control areas and with theirneighbours through the adequate development oftheir transmission networks.

The network analysis in this section focuses on thefour project countries: Albania, the former YugoslavRepublic of Macedonia, Montenegro and Serbia. How-ever, representative trade flows with neighbouringcountries are also included in the assessment (e.g.

with Romania and Bulgaria). The main network ele-ments in the region are presented in Figure 17.

Commercial congestion is permanently present inflow directions from Romania to Serbia and from Bul-garia to Serbia, due to the fact that Romania and Bul-garia have a surplus of electrical energy, and thatSerbia is used as a transit area towards Montenegro,the former Yugoslav Republic of Macedonia andGreece (countries with an electrical energy deficit).

Prior to October 2004, the SEE power system was notconnected for unified parallel operation. Following re-connection with the first synchronous zone of theUnion for the Coordination of Transmission of Elec-tricity (UCTE) in October 2004, power system condi-tions in SEE changed dramatically. Power utilities inthe region began a process of deregulation and pri-

Figure 17 Geographical coverage of the network analysis

Page 43: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro42

vatisation. Due to the post-socialist collapse in indus-trial consumption, the SEE region was initially charac-terised by a surplus of installed generation capacity.Relatively cheap electricity from SEE became a greatmarket opportunity. Countries in the region agreed tocreate a stable common regulatory and marketframework capable of attracting investment in powergeneration and transmission networks.

All these factors have a substantial impact on the op-eration and development of the regional transmissionnetwork. Compared to the other European regions,SEE is characterised by large interconnection capaci-ties at a 220 kV voltage level and above.

Planned new network elements

There are comprehensive, realistic plans for the de-velopment of the transmission network in SEE, andcurrent practice suggests that these developmentplans are more or less being implemented. Asidefrom the fact that the countries in the region can beregarded as well connected, new investments are ex-

pected, especially for cross-border elements or inter-nal connections that will have a significant impact oncross-border capacities.

The planned new transmission lines, listed in accor-dance with the ENTSO-E Ten-Year Network Develop-ment Plan (TYNDP) and strategic development andinvestment projects in each country, are shown in Figure 18.

In the three SLED scenarios (REF, CPP and AMB), gen-eration capacities — both distributed RES generationand conventional generation — and the assumedtotal electricity consumption change according to theagreed scenario definitions. The introduction of thesechanges in the network model has many impacts,which are assessed under the following categories:

Steady-state and contingency analyses

Evaluation of NTC

Calculation of transmission grid losses

The detailed network modelling methodology forthese three areas is presented in the Annex followingthe network modelling description.

Figure 18 Planned interconnection lines in South Eastern Europe

Page 44: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 43

Results of network modellingThe winter and summer operating regimes for the2015, 2020 and 2025 development stage in all scenar-ios were assessed in the network modelling stage. Theyear 2015 was considered as the reference year in theassessment, reflecting the present network topologyand the currently available generation capacities.

Steady-state and contingency analyses

Calculations within system studies were conductedon regional network models for SEE prepared for2020 and 2025. The power systems of the four as-sessed countries were modelled according to the datacollected and the Southeast Europe Cooperation

Initiative (SECI) regional model for 2020/2025, theavailable respective national development plans, andthe transmission system development set in theENTSO-E TYNDP 2012–2022.

System balances

Power system balances (in MW) in the assessed coun-tries, analysed for all regimes (winter and summer)and scenarios, are presented below.

In 2020:

Montenegro is an importing country in the summer

regime, while in the winter regime it is an exportingcountry, due to the significant number of RES.

Serbia is an exporter of 1,000 MW in both regimes.

Table 9 Contingencies in 2020

Scenario2020 Tripping Overloading Solution

REF

Winter max OHL 220 kV Fierza (AL)–Titan (AL) OHL 220 kV VauDejes (AL)–Komani (AL) New OHL 220 kV Komani (AL)–Titan (AL)

Summer max

OHL 400 kV Podgorica (ME)–Tirana (AL) OHL 220 kV Podgorica (ME)–Koplic (AL) Remedial action; Disconnection of theOHL 220 kV Podgorica (ME)–Koplic (AL)

OHL 220 kV Zrenjanin (RS)–WPP (RS) OHL 220 kV HIP (RS)–Beograd8 (RS) Changing of the conductors and earthwires and OPGW across the Danube River

with higher capacity (1 km)

CPP

Winter max OHL 220 kV Komani (AL)–Kolace (AL) OHL 220 kV VauDejes (AL)–Komani (AL) New OHL 220 kV Komani (AL)–Titan (AL)

Summer max

OHL 220 kV Komani (AL)–Kolace (AL) OHL 220 kV VauDejes (AL)–Komani (AL) New OHL 220 kV Komani (AL)–Titan (AL)

OHL 400 kV Pancevo (RS)–Beograd20 (RS) OHL 220 kV HIP (RS)–Beograd8 (RS)Changing of the conductors and earthwires and OPGW with higher capacity

(14.5 km)

OHL 400 kV Drmno (RS)–Smederevo (RS)

OHL 220 kV WPPs (RS)–Zrenjanin (RS)Changing of the conductors (on

WPPs–Zrenjanin) and earth wires andOPGW with higher capacity (44 km)

OHL 400 kV Mladost (RS)–TENT B (RS)

TR 400/220 SS Pancevo (RS)

OHL 220 kV WPPs (RS)–Pancevo (RS)

OHL 220 kV WPPs (RS)–Zrenjanin (RS) OHL 220 kV WPPs (RS)–Pancevo (RS)Changing of the conductors (on

WPPs–Pancevo) and earth wires andOPGW with higher capacity (22 km)

AMB

Winter max OHL 220 kV Komani (AL)–Kolace (AL) OHL 220 kV VauDejes (AL)–Komani (AL) New OHL 220 kV Komani (AL)–Titan (AL)

Summer max OHL 220 kV HIP (RS)–Beograd8 (RS)Changing of the conductors and earthwires and OPGW across the Danube River

with higher capacity (1 km)

Page 45: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro44

Albania is an exporting country.

Due to new capacities (conventional, especially TPPs)in 2025:

Serbia becomes a large exporter.

Montenegro is an exporter in the winter peak

regime (due to a certain number of RES), but in thesummer peak regime it still imports a smallamount of power.

Albania only exports in the winter peak regime

(AMB and REF) at 150 MW, and in other regimes itis balanced.

The former Yugoslav Republic of Macedonia is an importer in all regimes and scenarios.

(N-1) Security criteria1

In 2015, there are no high-loaded elements at 220 kVand 400 kV voltage levels in the assessed countries.

The results of the security assessments for 2020 and2025 are shown in Tables 9 and 10 for the whole ofthe assessed region, as contingencies appear at regional but not at country level.

In 2020, the following strengthening is necessary:

In all scenarios, the tripping of the OHL 220 kV

Fierza (AL)–Titan (AL) line leads to the overloadingof the OHL 220 kV VauDejes (AL)–Komani (AL) line.The new OHL 220 kV Komani (AL)–Titan (AL) linesolves this problem (70 km).

Some windfarms that are to be constructed within

Table 10 Contingencies in 2025

Scenario2025 Tripping Overloading Solution

REF

Winter max OHL 220 kV Fierza (AL)–Titan (AL) OHL 220 kV VauDejes (AL)–Komani (AL) New OHL 220 kV Komani (AL)–Titan (AL)

Summer max

OHL 220 kV WPPs (RS)–Zrenjanin (RS) OHL 220 kV HIP (RS)–Beograd8 (RS)

Changing of the conductors (on OHL 220kV HIP–BG8) and earth wires and OPGWacross the Danube River with higher

capacity (1 km)

OHL 400 kV RP Drmno (RS)–Smederevo (RS) OHL 400 kV Pancevo (RS)–Beograd (RS)

Changing of the conductors and earthwires and OPGW across the Danube River

with higher capacity (1 km)

CPP

Winter max

OHL 220 kV Komani (AL)–Kolace (AL) OHL 220 kV VauDejes (AL)–Komani (AL) New OHL 220 kV Komani (AL)–Titan (AL)

Several contingencies OHL 220 kV HIP (RS)–Beograd8 (RS)Changing of the conductors (on OHL 220kV HIP–BG8) and earth wires and OPGWwith higher capacity (whole line 14.5 km)

Summer maxOHL 400 kV Pancevo (RS)–Beograd20 (RS)

OHL 220 kV HIP (RS)–Beograd8 (RS)Changing of the conductors (on OHL 220kV HIP–BG8) and earth wires and OPGWwith higher capacity (whole line 14.5 km)OHL 220 kV WPPs (RS)–Zrenjanin (RS)

AMB

Winter max

OHL 220 kV Komani (AL)–Kolace (AL) OHL 220 kV VauDejes (AL)–Komani (AL) New OHL 220 kV Komani (AL)–Titan (AL)

Several contingencies OHL 220 kV HIP (RS)–Beograd8 (RS)Changing of the conductors (on OHL 220kV HIP–BG8) and earth wires and OPGWwith higher capacity (whole line 14.5 km)

Summer max

OHL 400 kV Pancevo (RS)–Beograd20 (RS) OHL 220 kV HIP (RS)–Beograd8 (RS)Changing of the conductors (on OHL 220kV HIP–BG8) and earth wires and OPGWwith higher capacity (whole line 14.5 km)

OHL 220 kV WPPs (RS)–Zrenjanin (RS) OHL 220 kV HIP (RS)–Beograd8 (RS)Changing of the conductors (on OHL 220kV HIP–BG8) and earth wires and OPGWwith higher capacity (whole line 14.5 km)

Page 46: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 45

the Serbian power utility EPS will be connected tothe OHL 220 kV Zrenjanin (RS)–Pancevo (RS) line.As a consequence of overloading in that area, inthe CPP scenario the conductor on the OHL 220kV Pancevo (RS)–Zrenjanin (RS) line should be re-placed with one with a higher capacity (length ofapproximately 22+44 km).

In the AMB scenario, only the replacement of a

1 km length of conductor on the OHL 220 kV HIP(RS)–Pancevo (RS) line is required (in addition tothe OHL 220 kV VauDejes [AL]– Komani [AL] line).

Generally speaking, the CPP scenario requires greateradditional investments than the other two (as a con-sequence of more new elements). The REF and AMBscenarios require the same level of investments, butless than the CPP scenario.

In 2025, the following strengthening is necessary:

In all scenarios, the tripping of the OHL 220 kV

Fierza (AL)–Titan (AL) line leads to the overloadingof the OHL 220 kV VauDejes (AL)–Komani (AL) line.The new OHL 220 kV Komani (AL)–Titan (AL) linesolves this problem (70 km).

Some windfarms to be constructed within the Ser-

bian power utility EPS will be connected to theOHL 220 kV Zrenjanin (RS)–Pancevo (RS) line. As aconsequence of overloading in that area, in theCPP and AMB scenarios the conductor on the OHL220 HIP (RS)–Beograd 8 (RS) line should be replaced with one with higher capacity (length ofapproximately 14.5 km).

The REF scenario requires less additional investmentthan the other two (as a consequence of fewer newelements). The CPP and AMB scenarios require thesame level of investments.

We can conclude from the results that the connectionof new RES causes some new overloading in Serbia andAlbania, while in Montenegro and the former YugoslavRepublic of Macedonia RES capacity development hasno impact on the 400 kV and 220 kV transmission net-work. Thus, for Montenegro, the newly installed RESgeneration capacities assumed in the scenarios do notpose problems to the electricity network. The presentsystem, with the planned line extensions, would beable to cope with the modelled electricity flows.

Net transfer capacity

According to the ENTSO-E methodology, the resultsof the gross transfer capacity (GTC) calculation should

be used for market analysis. However, since in thecurrent operation of the power systems NTC valuesare used to describe limitations in transfer capacitiesbetween countries, NTCs were calculated on the bor-ders of the analysed countries. These capacities wereused as inputs in the market analysis.

Capacity calculation is always related to a given powersystem scenario — that is, generation schedule andpattern, consumption pattern and available networkstate. These constitute the data that make it possibleto build up a mathematical model of the power sys-tem (load flow equations). The solution of this modelprovides knowledge of the voltages in the networknodes and the power flows in the network elements,which are the parameters monitored by a TSO inorder to assess system security.

Before the results are presented, it is important to un-derline that NTC values, beside the network topolo-gies, depend on the generation pattern of the regionas well as the engagement of the generation units inone particular system.

The NTC values for the three assessed scenarios for2020 and 2025 are presented in Figures 19 to 22.

The NTC values for the AMB and CPP scenarios arehigher than for the REF scenario on most of the bor-ders for both the winter and summer regimes. Theoverall conclusion for 2020 is that the replacement ofthe conventional sources with RES increases NTC val-ues on most of the borders, except in the directionMontenegro–Albania, where there is a slight decrease.

Similarly to 2020, in 2025 the deployment of renew-ables increases NTC values on most of the borders inboth the winter and summer regimes. In the case ofthe Albania–Montenegro direction there is a slight decrease in NTC values in the AMB scenario comparedto the REF scenario for both the winter and summerregimes. In both regimes, the highest increase is in theSerbia–Montenegro and Serbia–Albania directions.

By modelling the scenarios, we can observe that in theMontenegrin electricity system a bi-directional changeis taking place. In the direction to Serbia, the CPP andAMB scenarios would increase the NTC values, whilein the direction of Albania the opposite effect takesplace by 2025. However, the Serbia–Montenegro di-rection is the stronger connection, thus in total theAMB scenario representing higher RES penetrationwould increase the overall NTC of the country.

Page 47: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro46

Figure 20 Net transfer capacity values for 2020 (summer regime)

Figure 19 Net transfer capacity values for 2020 (winter regime)

Page 48: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 47

Figure 21 Net transfer capacity values for 2025 (winter regime)

Figure 22 Net transfer capacity values for 2025 (summer regime)

Page 49: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro48

Transmission grid losses

Transmission losses were calculated for all fouranalysed countries. The analyses were carried out forthree scenarios with different levels of RES, tworegimes (winter maximum and summer maximum)and three target years (2015, 2020 and 2025).

The total losses in Montenegro’s power systems areshown in Table 11.

The losses are highly dependent on electricity exchanges, transmission reinforcements, levels ofproduction and consumption, as well as the connec-

tion points between power plants and consumers.Power losses are higher in the winter regime andlower in the summer regime due to the large exchanges between the countries during the winterregime in the period 2015–2030.

An increase in RES in overall installed capacities, presented through the three scenarios, will producehigher transmission losses in gross consumption inthe case of Montenegro in 2020. A regional compari-son of losses can be found in the regional study.

The total annual losses in Montenegro’s power systems are shown in Figure 23.

Table 11 Transmission losses in 2015, 2020 and 2025 in Montenegro, for all scenarios and regimes

2015 2020 2025

Winter Summer Winter Summer Winter Summer

Equivalent duration time of maximum losses (h) 3,133 2,171 3,133 2,171 3,133 2,171

Transmission losses

(MW)

REF 19.3 16.5 38.4 38.7 39.1 34.4

CPP - - 35.4 32.6 34.9 30.8

AMB - - 35.7 38.5 34.1 29

Yearly transmissionlosses (GWh)

REF 96.3 204.3 197.2

CPP - - 181.7 176.2

AMB - - 195.4 169.8

Page 50: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 49

notEs1 (N-1) Security criteria refer to the assessment of the electricity system when the largest capacity (either network or generation) is removed

from the system to simulate the state of the system with the outage of the largest capacity element. In this case, an outage of a networkelement is modelled

Figure 23 Annual transmission losses in Montenegro for all scenarios

Page 51: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

VIII. Annex

Page 52: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 51

The two applied models — the EEMM and the EKCnetwork model — are described in greater detail inthis annex.

The European Electricity Market ModelThe EEMM simulates the operation of a Europeanelectricity wholesale market. It is a partial equilibriummodel.

Geographical scope

Figure 24 shows the geographical coverage of themodel. In the countries coloured orange, electricityprices are derived from the demand–supply balance.In the other group of countries, shown in blue, pricesare exogenous.

Market participants

There are three types of market participant in themodel: producers, consumers and traders. Marketsare assumed to be perfectly competitive — that is, actors are price takers.

Producers are the owners and operators of power

plants. Each plant has a specific marginal cost of production, which is constant at the unit level, andgeneration is capacity constrained at the level of in-stalled capacity.

The EEMM works with power plants at the unit level,and there are close to 5,000 power plant units in themodel. For individual power plants, the following es-sential information is contained by the model: in-stalled capacity, year of construction, technology andmain fuel type.

Within the electricity sector we can distinguish 12 dif-ferent technologies: biomass-fired power plants; coal-fired plants; lignite-fired plants; geothermal plants;heavy fuel oil–fired plants; light fuel oil–fired plants;hydropower plants; wind power plants; solar powerplants; nuclear plants; natural gas–fired plants; andtidal power plants.

The model takes into account short-term variablecosts with the following four main components: fuelcosts; variable OPEX; excise tax; and CO₂ costs (whereapplicable). The fuel cost in each generation unit de-pends on the type and price of the fuel and the overallefficiency of electricity generation. The latter is takenfrom the literature and empirical observation for var-ious power plant types and commissioning dates.

Figure 24 Analysed countries

Page 53: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro52

When the market price is above the marginal genera-tion cost of a unit, the unit is operated at full availablecapacity, and if the price is below the marginal costthere is no production.

Consumers are represented in the model in an aggre-gated way by price-sensitive demand curves. The slope of the demand curve is the same for allcountries. When determining future consumption, weconsider the relationship between past GDP and elec-tricity consumption figures separately for each coun-try. Based on this relation and the GDP forecast, we establish the expected annual electricity con-sumption.

Finally, traders connect the production and con-sumption sides of a market, export electricity tomore expensive countries and import it fromcheaper ones. Within the model, a country appearsas a node — that is, there are no network constraintswithin the country, only between countries. Cross-border trade takes place on capacity-constrained in-terconnectors between neighbouring countries.Electricity exchanges occur until either prices, net ofdirect transmission costs or export tariffs, equaliseacross the markets; or the transmission capacity ofthe interconnector is reached.

Equilibrium

The model is a partial equilibrium model and calcu-

lates the equilibrium allocation in all domestic elec-tricity markets under the following constraints:

Producers maximise their short-term profits,

given market prices.

Total domestic consumption is given by the aggre-

gate electricity demand function in each country.

Electricity transactions (exports and imports)

occur between neighbouring countries until mar-ket prices are equalised or transmission capacityis exhausted.

Energy produced and imported is in balance with

energy consumed and exported.

Market equilibrium always exists and is unique in the model.

The calculated market equilibrium is static: it only de-scribes situations with the same demand, supply andtransmission characteristics. To simulate the pricedevelopment of more complex electricity products,such as those for base-load or peak-load delivery, weperform several model runs with typical market pa-rameters and take the weighted average of the resulting prices.

When modelling, hourly markets are simulated, andthese simulations are independent from each other— that is, ramp-up costs are excluded. Within themodel, the equilibrium for a given hour (with respectto quantities and prices) is reached simultaneously bythe producer and transmission segments. Figure 25

Figure 25 Operation of the model

Output

Inpu

t

Marginal generation cost Available generation capacity

Supply curves by countryDemand curves by countryCross-border transmission capacity

Model

Equilibriun prices by country Electricity trade between countries Production by plant

Page 54: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 53

describes the operation of the model.

By determining the short-run marginal cost and avail-able capacity for each power plant we can constructthe supply curve for each country — in other words,the merit order curve. Taking into consideration theconstraints of cross-border capacities and the de-mand curves characterising each country, we arriveat the input parameters of the model. The model ap-plies these data to maximise European welfare, whichis the sum of producer and consumer surpluses. As aresult of model computations we get the hourly equi-librium price for each country, the hourly commercialtransfers between the countries, and the productionof each power plant unit.

We simulate the short-term market represented by aselected hour. We typically aim to model an annualperiod, rather than a single hour, therefore on the de-mand side it is necessary to settle on a given numberof reference hours through which annual averageprices are approximated. In the model, 90 referencehours are established.

Network representation

The EEMM assumes that each country is a node — inother words, network constraints do not exist withinany of the countries. Cross-border capacities, on theother hand, may impose a serious limitation on thetrading of electricity. Scarcity is expressed through the NTC.

The EKC model will provide modelled NTC values forthe four target countries of the SLED project and theneighbouring regions (directly connected to the targetcountries), while for the rest of the countries mod-elled by the EEMM, data from ENTSO-E will be used.

The EKC network modelA regional load-flow model on which analyses are per-formed was developed based on SECI regional trans-mission models for 2015 (also used as the currentmodel), 2020 and 2025, updated according to as-sumptions of the ToR.

All analyses were performed for 2015, 2020 and 2025,with two typical regimes: winter peak (third Wednes-day in January at 19:30), and summer peak (thirdWednesday in July at 10:30).

The topology of transmission networks in SEE coun-

tries (Albania, Bosnia and Herzegovina, Bulgaria,Croatia, Greece, the former Yugoslav Republic ofMacedonia, Romania and Serbia) is taken accordingto the SECI regional model, updated according to gen-eration surplus projections in the SEE region. Otherneighbouring countries (France, Switzerland, Ger-many, Ukraine and Slovakia) are modelled as injec-tions (over interconnection lines); while Austria andHungary are presented with the full model adoptedaccording to the UCTE system adequacy forecast2014–2024.

The system study was performed on already existingstudies using the current regional system models de-veloped under SECI, checked and updated by theTSOs. System studies and planning were done on aregional basis, as was the definition of the bordercrossing points.

Electric power systems in SEE were modelled withtheir complete transmission networks (at 400 kV, 220 kV, 150 kV). The power systems in the four assessed countries were modelled in addition at the110 kV voltage level. The network equivalent of Turkey(i.e. European part) and the rest of ENTSO-E Continen-tal Europe (modelled over the X-node injections) werealso used in the model.

The following assessment was carried out in the net-work study:

Load-flow data collection, which includes:

an assessment of the existing electricity network•situation within Albania, the former Yugoslav Re-public of Macedonia, Montenegro and Serbia,together with the regional context; and

a definition of the network topologies and•regimes for 2015, 2020 and 2025, using realisticscenarios for demand growth, generation expansion, transit flows, RES integration andHVDC links.

TTC/NTC evaluation among Albania, the former

Yugoslav Republic of Macedonia, Montenegro andSerbia in all directions, for all topology scenarios,with reference to each target year and regime.

An assessment of transmission grid losses with

and without a level of energy production from RES.

Load-flow data collection

In the process of collecting the data needed for load-flow studies, representatives of the four countries reviewed and updated the proposed datasets,

Page 55: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro54

which include:

Demand level in the agreed regimes and power

exchanges in 2015, 2020 and 2025 for two charac-teristic regimes:

third Wednesday in January at 19:30 (winter•peak); and

third Wednesday in July at 10:30 (summer peak).•

A list of new generation facilities and generation

units to be decommissioned up to 2015, 2020 and2025.

A list of new elements in the transmission network.

The level of transmission reliability margin used in

the evaluation of the NTC.

These data were used for the preparation of the net-work models for 2015, 2025 and 2025, which wasused for the load-flow analyses.

Demand

The development of demand in two characteristicregimes (third Wednesday in January at 19:30 [winterpeak] and third Wednesday in July at 10:30 [summerpeak]) in 2015, 2020 and 2025 will be analysed on thebasis of:

ENTSO-E online datasets;

ENTSO-E scenario outlook and adequacy fore-

casts;

national demand projections; and

consultants’ datasets from relevant projects in the

SEE region.

Since network forecast models are used in our analy-sis, demand excludes transmission and distributionlosses, as well as the power plants’ own consumptionand pumping.

In the Montenegrin power system, the operation ofthe KAP aluminium smelter (with an installed capacityof 220 MW) has a big influence on system demand (atfull capacity it represents 20 percent of the maximumpower consumption, or 50 percent at minimumpower consumption).

Network modelling methodologyThe network modelling methodology comprises threeparts:

steady-state and contingency analyses;

evaluation of NTC; and

calculation of transmission grid losses.

These parts are introduced in detail below.

Steady-state and contingency analyses

For the defined scenarios, steady-state load flows arecalculated and contingency (n-1) analyses performed.Security criteria were based on the loadings of linesand voltage profile, and were checked for each scenario analysed.

Load-flow analyses provide an insight into transmis-sion network adequacy for the observed scenarios ofexchanges and a comparison of observed configura-tions, under steady-state and (n-1) operating condi-tions.

Load-flow assessment is a basic step in NTC evalua-tion and comprises the following analyses:

steady-state AC load flow;

security (n-1) assessment; and

voltage profile analysis.

In the analysis of voltage profiles, voltage limits aretaken according to the respective national grid codes.

It should be stressed that only the 400 kV and 220 kVnetworks were assessed from a security point of view.There are many new RES to be connected to lower-voltage networks, which might cause problems in net-works of 110 kV or lower, although this should besolved via the national transmission network plans.

Evaluation of net transfer capacity

The TTC and NTC were evaluated between Albania,the former Yugoslav Republic of Macedonia, Mon-tenegro and Serbia, as well as between these coun-tries and their neighbours, in all directions, for alltopology scenarios, and with reference to each targetyear and regime. A final assessment was also madeof the TTC/NTC additional values as a result of new in-terconnections and the strengthening of the majorenergy transit routes.

It is also important to note that TTC, NTC, base caseexchange (BCE), already allocated capacity (AAC) andavailable transfer capacity (ATC) are the exchangeprogramme values; these are not the physical flowsand generally differ from the physical flows at the in-terconnection lines (except in particular cases of radial operation).

Page 56: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Montenegro DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor 55

The solution of this model is the so-called base caseand is the starting point for the computation. Thisbase case can already contain exchange programmesbetween TSOs and control areas. These are the vari-ous transactions likely to exist in the forecasted situa-tion according to what has been observed in the past.

The TTC value may therefore vary (increase or decrease) when approaching the time of programmeexecution as a result of a more accurate knowledgeof generating unit schedules, load pattern, networktopology and tie line availability.

The general definitions of transfer capacities (TTC,NTC) and the procedures for their assessment are ac-cording to ENTSO-E, and the practice and experienceof regional SEE TSO working groups.

BAsE cAsE ExchAngE

In the base case, for a given pair of neighbouring con-trol areas A and B, for which capacities are to be com-puted, the global exchange programme known as BCEexists. The BCEs are the programme (contractual) values related to the base case model.

MAxIMuM ADDItIonAL ExchAngE (ΔEMAx)

The maximum additional programme exchange (overthe BCE) that meets the security standards is indi-cated by ΔEmax. An additional programme exchangeis performed by decreasing generation in area A, andsimultaneously increasing generation in area B.

totAL trAnsFEr cAPAcIty

The TTC is the maximum exchange programme be-tween two areas, compatible with the operational se-curity standards applicable to each system, if futurenetwork conditions, generation and load patterns areperfectly known in advance.

TTC = BCE + ΔEmax

trAnsMIssIon rELIABILIty MArgIn

The TRM is a security margin that deals with uncer-tainties in the computed TTC values arising from:

unintended deviations in physical flows during

operation due to the physical functioning of loadfrequency control (LFC);emergency exchanges between TSOs to deal with

unexpected unbalanced situations in real time; andinaccuracies, for example in data collection and

measurements.In the present study, the TRM value used will be ac-cording to the collected load flow data sent by theTSOs.

nEt trAnsFEr cAPAcIty

The NTC is the maximum exchange programme be-tween two areas compatible with the security stan-dards applicable in both areas, taking into account thetechnical uncertainties in future network conditions.

NTC = TTC-TRM

Transmission grid losses

The assessment of electricity losses is based on theequivalent duration time of losses in winter peak andsummer peak periods. This approach takes into ac-count that the impact on losses can be different inthese two regimes, meaning that annual losses canbe determined more accurately.

The assessment of electricity losses is based on theequivalent duration time of maximum losses. Themethod used to determine this equivalent durationtime requires two parameters as input: maximum demand and load factor. These two parameters are ob-tained from an analysis of the load duration diagram ofthe analysed year for the respective power system.

Yearly losses are calculated based on grid losses inMW calculated for the two analysed regimes —winterpeak and summer peak — and the equivalent loadduration time of the respective loads in theseregimes. With the calculated equivalent duration timeof maximum losses for the respective period, yearlytransmission grid losses (GWh) are calculated by multiplying this value by power losses (MW):

- Active power losses in MW in specific regime i

- Equivalent duration time in hours for the respec-tive load in regime i

Page 57: Decarbonisation modelling in the electricity sectordocuments.rec.org/publications/SLED_Montenegro_ELEC_ENG.pdf · 8 DEcArBonIsAtIon MoDELLIng In thE ELEctrIcIty sEctor Montenegro

Decarbonisation modelling in the electricity sector

Montenegro

Support for Low-Emission Development in South Eastern Europe (SLED)

MO

NTE

NEG

RO

EN

G