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Annex 4 analytical methods

model description

general description

acronym
JRC-EU-TIMES
name
JRC TIMES energy system model for the EU
main purpose
Designed for analysing the role of energy technologies and their innovation for meeting Europe's energy and climate change related policy objectives.
homepage

Developer and its nature

ownership
Third-party ownership (commercial companies, Member States, other organisations, …)
ownership additional info
The database with inputs is owned by JRC (Excel files). These files will be made open in 2019. The TIMES code is owned by ETSAP. This code is open in a sense that anyone can request the code after signing a letter of agreement. The TIMES code is not open in a sense that it cannot be redistributed. Other third party software is needed:VEDA or ANSWER software for data and result handling.
is the model code open-source?
NO

Model structure and approach with any key assumptions, limitations and simplifications

details on model structure and approach

The JRC-EU-TIMES is a model of the energy system within the EU28 and certain neighbouring countries (Iceland, Norway, Switzerland and the Western Balkans). It provides a coherent framework to quantitatively assess the development needs for each of the identified technology sectors under different climate and energy pathways in Europe, up to 2050.

The TIMES model generator from ETSAP allows for a detailed techno-economic description of resources, energy carriers, conversion technologies and energy demands. TIMES-based energy system models include upstream energy flows up to the level of resource-mining and imports. After its transformation from primary energy (through refineries and power plants, among other technology options), final energy can be consumed within different economic sectors (e.g. residential, tertiary/services, industry or transportation). An important difference to other models which cover only a single subsector of the energy system is that in TIMES the subsectors can interact with each other.

The JRC-EU-TIMES database contains:

  1. JRC-EU-TIMES logic: includes those specific equations (and relationships) between different variables of the model which are not included in the general TIMES model generator from ETSAP. Specific equations introduced by JRC include, for example, relationships between the operation of dispatchable power plants and the amount of variable power generation (e.g. from certain RES).
  2. JRC-EU-TIMES data: includes fixed numeric techno-economic parameters representing the energy system such as:
    1. End-use energy services and materials’ demand
    2. Present and future sources of primary energy supply and their potentials
    3. Key characteristics of existing and future energy-related technologies, such as efficiency, technological stock, availability, investment costs, O&M (operation and maintenance) costs and discount rates
    4. Policy constraints, such as emission limits or energy efficiency targets and other policy assumptions.

The JRC-EU-TIMES model solves an optimisation problem for the horizon 2005-2065 by minimising the total discounted energy-system cost needed to meet the future demand for energy services. The energy-system cost includes investments in supply and demand technologies, operational expenses and fuel costs. The optimisation horizon is divided into 9 periods. Each period consists of equal years that are divided in 12 time-slices that represent an average of day, night and peak demand for each of a year’s four seasons. To address flexibility issues, each time-slice of the power sector is further split into two sub-periods – this additional dimension allows differentiation of situations where variable RES electricity generation exceeds demand from those situations where this is not the case. Using this approach, the JRC-EU-TIMES model is able to model and compare curtailment with different transformation or storage options in cases of excessive variable RES electricity production.

TIMES family based energy system models are used (i) in the member states and non-EU countries (e.g. UK, France, Spain, Germany, Italy, Japan, US) to model energy policy scenarios, (ii) in the private sector (e.g. EdF) to support decisions on investment priorities, (iii) in international organisations (e.g. IEA) to model future technology scenarios in order to meet certain decarbonisation targets. More information on the TIMES family of model can be found on the IEA Energy Technology website, http://www.iea-etsap.org/web/index.asp More information on the JRC-EU-TIMES model can be found in the JRC Science and Policy report The JRC-EU-TIMES model - Assessing the long-term role of the SET Plan Energy technologies (JRC85804, http://publications.jrc.ec.europa.eu/repository/handle/JRC85804)

model inputs

The model is supported by a detailed database, with the following exogenous inputs:

  • End-use energy services and materials demand, such as residential lighting, machine drive requirements or steel; The materials and energy demand projections for each country are differentiated according to economic sector and end-use energy service. These were generated by the macroeconomic projections from the GEM-E3 model at JRC IPTS. These are: GDP growth; private consumption as a proxy for disposable income; price evolution and sector production growth for industry, services, transports and agriculture. In TIMES, these macroeconomic drivers are transformed into the different final annual end-use demand projections. The residential sector requires a more detailed approach to generate the demand for heat, cooling and hot water, since they depend on the characteristics of the dwellings. The projection of energy end-uses for the residential sector involves several steps:the projection of the number of dwellings and their allocation by category (rural, urban single house or urban apartments); the projection of the heat/cooling/hot water demand per dwelling by category, and the projection of the total demand.The main data sources are EUROSTAT and several National Statistics Institutes, as well as other existing databases such as ENTRANZE, TABULA, and the BPIE Buildings Performance Institute Europe.
  • Characteristics of the existing and future energy related technologies, such as efficiency, stock, availability, investment costs, operation and maintenance costs, and technology-specific discount rate; The energy supply and demand technologies for the base-year (2005) are characterised considering the energy consumption data from EUROSTAT to set sector specific energy balances to which technologies profile must comply. Information on installed capacity, efficiency, availability factor, and input/output ratio were introduced using diverse national sources. This was followed by a bottom-up approach that adjusted the technologies specifications to achieve coherence with official energy statistics. This bottom-up approach was very relevant for the residential and commercial sectors, for which there is less detailed information on existing technologies. The energy supply and demand technologies beyond the base year are compiled in an extensive database with detailed technical and economic characteristics of new energy technologies. The two most relevant sources of this database are the Energy Technology Database (for electricity generation) hosted at JRC-IET and the JRC-IET periodic publication ETRI - Energy Technology Reference Indicators projections for 2010-2050. The technology-specific discount rates are aligned to those used in the PRIMES model and that underlie the EU Reference Scenarios (EU Energy, transport and GHG emissions. Trends to 2050).
  • Present and future sources of primary energy supply and their potentials; The present and future sources of primary energy and their constraints (fossil and renewable energy) for each country are from derived from several sources. For renewables, the maximum potentials come from the NEEDS project, updated with IET experts' own assumptions. For selected renewables (biomass and solar, wind forthcoming) the potentials have been derived following a detailed and transparent methodology with experts' inputs.
  • Policy constraints; The policy constraints as CO2 emission caps, tax, subsidies and emission trading are user-defined and can be tailored for each particular policy question. The typical configuration of the model include a current policy initiative scenario, implementing agreed emission reduction, renewable energies, and energy efficiency targets; and strong decarbonisation scenarios. Targets for the penetration of specific renewable technologies can also be implemented. 
model outputs

The most relevant outputs are

  • the annual stock and activity of energy supply and demand technologies for each region and period.
  • associated energy and material flows including emissions to air and fuel consumption, detailed for each energy carrier.
  • Besides technical outputs, for every year is obtained the associated
    • operation and maintenance costs
    • the investment costs for new technologies
    • all energy and materials commodities prices (including for emissions if an emission cap is considered).

Intended field of application

policy role

The model is designed for analysing the role of energy technologies and their innovation for meeting Europe's energy and climate change related policy objectives. It models technology market uptake and their interaction with the energy infrastructure including storage options in an energy systems perspective. It is a relevant tool to support impact assessment studies in the energy policy field that require quantitative modelling at an energy system level with a high technology detail.

The model can support the implementation of the Energy Union roadmap, in particular with a focus on A new European energy R&I approach to accelerate energy system transformation, composed of i) an integrated Strategic Energy Technology (SET) Plan and ii) a strategic transport R&I agenda.

In this context, the JRC-EU-TIMES model could contribute to analysis on: technology deployment and thresholds for innovation; employment opportunities in the renewable energy sector.

policy areas
  • Climate action 
  • Energy 
  • Environment 

Model transparency and quality assurance

Are uncertainties accounted for in your simulations?
YES - Previous JRC reports have shown how uncertainty of cost and efficiency parameters impact technologies' competitiveness.
Has the model undergone sensitivity analysis?
YES - The model's paradigm can be called robust as shown by different peer reviewed scientific papers.
Has the model been published in peer review articles?
YES - The model was validated by colleagues from within the Commission as well as people from IEA, Lulea University of Technology, ECN, ETI, EDF, CRES, Fraunhofer ISI and ENERIS.
Has the model formally undergone scientific review by a panel of international experts?
NO
Has model validation been done? Have model predictions been confronted with observed data (ex-post)?
NOT_APPLICABLE - JRC-EU-TIMES does not estimate any probability of occurrence for the scenarios and its goal is not to do forecasts for the short term.
To what extent do input data come from publicly available sources?
Based on both publicly available and restricted-access sources
Is the full model database as such available to external users?
NO - A public version of the JRC-EU-TIMES database is under investigation.
Have model results been presented in publicly available reports?
YES
Have output datasets been made publicly available?
YES - Examples or the baseline scenario of the Heatroadmap project as well as the runs for the future Low Carbon Energy Observatory project.
Is there any user friendly interface presenting model results that is accessible to the public?
NO
Has the model been documented in a publicly available dedicated report or a manual?
YES - All assumptions are documented in a model description from 2013 and in follow up papers.

Intellectual property rights

Licence type
Non-Free Software licence

application to the impact assessment

Please note that in the annex 4 of the impact assessment report, the general description of the model (available in MIDAS) has to be complemented with the specific information on how the model has been applied in the impact assessment.

See Better Regulation Toolbox, tool #11 Format of the impact assessment report).