Annex 4 analytical methods

model description

general description

acronym
POLES
name
Prospective Outlook for the Long term Energy System
main purpose
POLES is a world energy demand and supply and greenhouse gas emissions model used for international energy and climate policy assessment.
homepage
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Developer and its nature

ownership
Co-ownership (EU & third parties)
ownership additional info
The model is developed and operated by the JRC. Research versions are developed in collaboration with the University of Grenoble-CNRS (GAEL laboratory), and some model upgrades have been done with Enerdata. University of Grenoble-CNRS and Enerdata run own versions for their specific use (not for informing EC policy and conducting IAs).  
is the model code open-source?
NO

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

details on model structure and approach

POLES is a global recursive dynamic simulation model of the energy system allowing simulating a wide range of energy and climate policies, being they on the demand side or in the supply sector. It displays a high regional resolution and sectoral representation, and provides endogenous simulation of all steps of the energy system by energy vector and sector: final energy demand, transformation (including power generation), trade, primary supply, international and final user prices, as well as the development of energy-consuming equipment. GHG emissions from fossil fuel combustion, industry, waste, agriculture and land use are also covered. Anthropogenic air pollution can also be covered.

model inputs

Main inputs are:  

  • Projection / framing conditions: population, GDP growth, economic structure, energy resources
  • Historical: socio-economic activity variables (mobility per transport mode, freight volumes, vehicles stock, buildings stock), energy balance (production, demand, transformation, power capacities, prices), technology costs, sectoral GHG emissions.
  • Parameters: demand function elasticities, energy efficiency technological trends, technology learning rate

Key input assumptions include socio-economics (population and growth of GDP) and energy resources.    Population is an exogenous driver, standard source used is the UN World Population.  GDP is also exogenous and is derived from various international sources. Latest work used GDP assumptions from: latest IMF forecasts (for the short run), OECD, or CEPII forecasts (for the longer run). Consistency with population is checked.  Energy resources come from various international sources, including BGR and USGS. 

The model also uses historical databases on energy production, energy demand, energy prices, energy trade, power generation capacities, GHG emissions and other key activity data (sectoral value added, mobility per mode, freight volumes, vehicles stock, buildings stock).  Assumptions on technology costs are also included, either as full prospective data series or as to inform endogenously recreated learning curves.  Additional parameters consist in econometric elasticities and policy-dependent energy efficiency improvement trends.

Finally, key inputs are bioenergy cost curves and land-related GHG emissions cost curves from the GLOBIOM model.

model outputs
  • Projected socio-economic activity variables: sectoral value added, tons of steel consumed and produced, mobility per transport mode, freight volumes, vehicles stock, buildings stock
  • Projected energy balance per country / region: energy production, energy demand, energy trade (in energy terms), energy transformation, power capacities, energy prices
  • Investment needs, technology costs, energy trade (in economic value)
  • Projected sectoral GHG emissions for energy, industry, agriculture and LULUCF

Intended field of application

policy role

POLES is designed to contribute primarily to the following policy areas:  Climate Action, Energy. It could also be used in the following policy areas: Agricultural, Environment, Trade, Transport.

POLES can be used to support policy anticipation and formulation by developing consistent global energy scenarios that feed in to policy developments in the field of energy and climate change. The model has been and is still very much used to assess the impact of European and international energy and climate policies on energy markets and GHG emissions, by DG CLIMA in the context of international climate policy negotiations and by DG ENER in the context of the EU Energy Union.

POLES has also been applied for the analyses of various Impact Assessments in the field of climate change and energy, among them: the Proposal for a revised energy efficiency Directive (COM(2016)0761 final)  and The Paris Protocol – A blueprint for tackling global climate change beyond 2020 (COM(2015) 81 final/2).

The model is being extended towards co-benefits of energy and climate policy in terms of land use and water use.

policy areas
  • Agriculture and rural development 
  • Climate action 
  • Energy 
  • Environment 
  • Transport 

Model transparency and quality assurance

Are uncertainties accounted for in your simulations?
NO - Different model runs can be done with different settings to represent uncertainty in model parameters.
Has the model undergone sensitivity analysis?
YES - In multiple occasions, batch runs have been done to test the model's reactiveness to different values of a single input parameter (carbon price, technology costs…).
Has the model been published in peer review articles?
YES - The model has participated in inter-model comparison exercises for many years, in which peers compare models' results and methodologies, and has participated in many peer-reviewed papers.
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 - Historic period (from 1990 to current year -1 or -2) is used to calibrate parameters that allow the model to endogenously reproduce observed patterns.
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 large part of input data is not public. The full list of data sources is available in the POLES-JRC manual. Additional data can be provided on demand.
Have model results been presented in publicly available reports?
YES
Have output datasets been made publicly available?
YES - Examples of output data made available are energy and GHG emissions balances provided with the GECO report(s), as well as a web interface to navigate results and access data on the GECO web site
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

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).