EEMM
Source: Commission modelling inventory and knowledge management system (MIDAS)
Date of Report Generation: Mon Apr 22 2024
Dissemination: Public
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Overview
Acronym
EEMM
Full title
European Electricity Market Model
Main purpose
EEMM is a dynamic, multi-market sectoral equilibrium model, simulating the European electricity wholesale markets and analyse the impact of policies on the European markets.
Summary
REKK’s EEMM is a partial equilibrium microeconomic model. It assumes that the electricity market is fully liberalised and perfectly competitive. In the model, electricity generation as well as cross-border capacities are allocated on a market basis without gaming or withholding capacity: the cheapest available generation is used, and if imports are cheaper than producing electricity domestically demand is satisfied from imports. Both production and trade are constrained by the available installed capacity and net transfer capacity (NTC) of cross-border transmission networks respectively. Due to these capacity constraints, prices across borders are not always equalised.
There are 41 countries (44 markets) modelled in EEMM: in these countries prices are derived from the demand-supply balance, while on outside markets we assume exogenous prices.
The EEMM model has an hourly time step, modelling 90 representative hours with respect to load, covering all four seasons and all daily variations in electricity demand. The selection of these hours ensures that both peak and base hours are represented, and that the impact of volatility in the generation of intermittent RES technologies on wholesale price levels are captured by the model.
There are three types of market participants in the model: producers, consumers, and traders. All of them behave in a price-taking manner: they take the prevailing market price as given and assume that their actions have a negligible effect on this price.
The model has been useful in assessing:
- Effects of different coal phase-out policies in Europe
- Cost-Benefit Analysis (CBA) of new infrastructure and cross-border cost allocation (CBCA)
- Electricity wholesale price forecast
- Effects of various fuel price assumptions (natural gas, coal) on the European electricity wholesale market
- Effects of the CO2 price on the European electricity wholesale market
- Effects of a new power plant/cross-border line on the European electricity market
Model categories
Energy
Model keywords
electricityenergy market modellinginfrastructure
Model homepage
Ownership and Licence
Ownership
Third-party ownership (commercial companies, Member States, other organisations, …)
Ownership details
Licence type
Non-Free Software licence
The license has one or more of the following restrictions: it prohibits creation of derivative works; it prohibits commercial use; it obliges to share the licensed or derivative works on the same conditions.
Details
Structure and approach
The European Electricity Market Model consists of the following building blocks:
Supply side:
For all given technologies (e.g. OCGT, CCGT, thermal) commissioning date defines the efficiency, the self-consumption and the variable OPEX cost for all units. Using the fuel prices as an input total fuel costs are calculated taking into account the above parameters. CO2 costs are based on the calculated emission level and the CO2 quota prices, and all these costs are then added to the total energy tax paid and the variable OPEX.
It is important to note that only short-term marginal costs are taken into account, the model does not analyse whether long-term operation is profitable or not. It is possible, that some units remain operational even if they provide electricity in a few hours per year. Power plant units are available until the end of their (pre-defined) lifetimes.
Demand side: When modelling the electricity system short-term market outcomes - representing only one hour - are simulated. However, typically yearly results are interesting, thus, reference hours are defined to be able to produce yearly outputs. In the EEMM 90 reference hours are used: there are six types of hours representing yearly differences, another 4 that represent daily seasonality and the 24 types of hours created this way are further separated to gain 90 representing hours. This latter separation is carried out in a way to gain as homogenous groups as possible, so the demand of all 8760 hours could be represented very well with the given 90 reference hours.
Demand is calculated for each reference hour as the arithmetic mean of the demand of the hours it represents in 2018, and then adjusted according to the level of yearly demand assumed for the modelled year. Yearly demand forecasts are based on EU’s PRIMES modelling for each country.
When modelling a whole year, the model runs 90 times, and outputs are saved for all reference hours separately. From these outputs yearly results are calculated taking into account the weight of all reference hours (based on how many hours they represent). This way yearly baseload prices, import-export positions and production of each unit are generated as outputs.
Cross-border trade
Power flow is ensured by 104 interconnectors between the countries, where each country is treated as a single node, thus no domestic power system constraint is taken into account. NTC values are used to indicate trading possibilities, seasonal differences are included in the modelling based on historical data from ENTSO-E Transparency Platform. Future investments are assumed based on data from ENTSO-E’s latest Ten-Year Network Development Plan (TYNDP).
Equilibrium
The model calculates the simultaneous equilibrium allocation in all markets with the following properties:
- Producers maximize their short-term profits given the prevailing market prices.
- Total domestic consumption is given by the aggregate electricity demand function in each country.
- Electricity transactions (export and import) occur between neighbouring countries until market prices are equalized or transmission capacity is 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.
Electricity product prices
The calculated market equilibrium is a static one: it only describes situations with the same demand, supply, and transmission characteristics. However, these market features are constantly in motion. As a result, short run equilibrium prices are changing as well.
To simulate the price development of more complex electricity products, such as those for base load or a peak load delivery, we perform several model runs with typical market parameters and take the weighted average of the resulting short term (hourly) prices.
Input and parametrization
Data for the modelling scenarios is derived from publicly available sources.
- NTC capacity data based on ENTSO database, including the ENTSO-E latest TYNDP projects effect on NTCs
- Supply side database are based on national regulators, system operators, and individual power company and plant websites. These information are cross-checked with aggregated database (ENTSO-E, Eurostat)
- Natural gas price forecast is based on EGMM (European Gas Market Modelling) modelling results
- Other fuel prices (coal and oil) and CO2 price forecast are based on international organizations (IMF, IEA, European Commission, etc.)
- Demand based on ENTSO-E fact database, forecasted consumptions are based on PRIMES projections
Main output
Outputs of modelling are the wholesale electricity wholesale market prices per country per reference hours and from this information also the yearly base and peakload prices can be determined. Electricity trades between countries and production and CO2 emission of all producers are also calculated. Based on those outputs the model also calculates welfare on country and stakeholder level (consumer, producer, traders).
Spatial & Temporal extent
The output has the following spatial-temporal resolution and extent:
| Parameter | Description |
|---|---|
| Spatial extent / country coverage | EU Member states 27NorwaySwitzerlandUnited KingdomAlbaniaArmeniaAzerbaijanBelarusBosnia and HerzegovinaFormer Yugoslav Republic of MacedoniaGeorgiaKosovoMoldovaMontenegroSerbiaUkraineTurkey |
| Spatial resolution | National |
| Temporal extent | Very short-term (less than 1 year)Short-term (from 1 to 5 years)Medium-term (5 to 15 years)Long-term (more than 15 years) |
| Temporal resolution | HoursYears |
Quality & Transparency
Quality
Model uncertainties
Models are by definition affected by uncertainties (in input data, input parameters, scenario definitions, etc.). Have the model uncertainties been quantified? Are uncertainties accounted for in your simulations?
- response
- yes
- details
- Sensitivity runs performed. These are dependent on the context and not the model itself
- url
Sensitivity analysis
Sensitivity analysis helps identifying the uncertain inputs mostly responsible for the uncertainty in the model responses. Has the model undergone sensitivity analysis?
- response
- yes
- details
- Sensitivity runs performed. These are dependent on the context and not the model itself
- url
Have model results been published in peer-reviewed articles?
- response
- yes
- details
- url
Has the model formally undergone scientific review by a panel of international experts?
Please note that this does not refer to the cases when model results were validated by stakeholders.
- response
- no
- details
- url
Model validation
Has model validation been done? Have model predictions been confronted with observed data (ex-post)?
- response
- yes
- details
- Ex post wholesale prices and electricity mix
- url
Transparency
To what extent do input data come from publicly available sources?
This may include sources accessible upon subscription and/or payment
- response
- Entirely based on publicly available sources
Is the full model database as such available to external users?
Whether or not it implies a specific procedure or a fee
- response
- no
- details
- Proprietary data collection based on public sources
- url
Have model results been presented in publicly available reports?
Note this excludes IA reports.
- response
- yes
- details
Have output datasets been made publicly available?
Note this could also imply a specific procedure or a fee.
- response
- no
- details
- url
Is there any user friendly interface presenting model results that is accessible to the public?
For instance: Dashboard, interactive interfaces...
- response
- no
- details
- url
Has the model been documented in a publicly available dedicated report or a manual?
Note this excludes IA reports.
- response
- no
- details
- Documentation included in annexes of respective studies and REKK website (except equations)
Is there a dedicated public website where information about the model is provided?
- response
- no
- details
- url
Is the model code open-source?
- response
- no
- details
Can the code be accessed upon request?
- response
- no
- details
The model’s policy relevance and intended role in the policy cycle
The model is designed to contribute to the following policy areas
- Energy
The model is designed to contribute to the following phases of the policy cycle
- Evaluation – such as ex-post evaluation
- Formulation – such as ex-ante Impact Assessments
- Implementation – this also includes monitoring
The model’s potential
The EEMM is a partial equilibrium microeconomic model. It assumes fully liberalised and perfectly competitive electricity markets. The model was used to evaluate the infrastructure developments triggered by the implementation of the TEN-E Regulation by measuring benefits (e.g. socio-economic welfare derived from the higher trading opportunities allowed by the new infrastructure). The main purpose of the modelling carried out for this study was to monetise the realised and potential benefits (in term of socio-economic welfare change) of the projects of common interest (PCIs). In addition, based on modelling outcomes, several indicators were calculated in order to illustrate the effect of the TEN-E Regulation on market integration, competition, CO2 emission reduction and RES integration.
Previous use of the model in ex-ante impact assessments of the European Commission
Use of the model in ex-ante impact assessments since July 2017.
2021SWD/2020/346 final/2
Impact assessment accompanying the document Proposal for a Regulation of the European Parliament and of the Council: on guidelines for trans-European energy infrastructure and repealing Regulation (EU) No 347/2013
- Lead by
- ENER
- Run by
- Regional Centre for Energy Policy Research
- Contribution role
- baseline and assessment of policy options
- Contribution details
The model helped to assess the following impacts:
- Cost/availability of essential inputs (raw materials, machinery, labour, energy, ..)
- Investment cycle
- Affects on individual Member States
- Investment flows & trade in services
- Cost of doing business
- Market share & advantages in international context
- Free movement of goods, services, capital and workers
- Competition
- Promotion of academic or industrial research
- Budgetary consequences for public authorities
- Consumer's ability to benefit from the internal market or to access goods and services from outside the EU
- Prices, quality, availability or choice of consumer goods and services
- Safety or sustainability of consumer goods and services
- Impact on vulnerable consumers
- Significant effects on sectors
- Impact on regions
- Disproportionately affected region or sector
- Investments and functioning of markets
- Emission of greenhouse gases
- Economic incentives set up by market based mechanisms
- Ability to adapt to climate change
- Use of renewable resources
- Use of non-renewable resources
- Environment in third countries
- Fuel mix used in energy production