Prospective Outlook for the Long term Energy System

The POLES model is a global sectoral simulation model for the development of energy and greenhouse gases scenarios until 2050 (2100 for research projects). It has been developed by the JRC since 1996, and JRC runs the POLES-JRC version, which also includes a module on emissions of air pollutants.    

The dynamics of the energy system are based on a recursive (year by year) simulation process of energy demand and supply with lagged adjustments to prices and a feedback loop through international energy prices. The model is developed within the framework of a hierarchical structure of interconnected modules at the international, regional and national level. It contains technologically-detailed modules for energy-intensive sectors, including power generation, non-metallic minerals and chemistry, as well as detail of energy uses in buildings and modal transportation sectors. The model also provides a complete coverage of greenhouse gas emissions: the detailed energy system gives the evolution of CO2 from fossil fuels combustion; emissions from industry are derived from the description of the economy structure while agriculture and land use emissions come from a reduced form of the specialist GLOBIOM model. All GHG emissions can be affected by climate mitigation policy.

The model supports 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 scenarios provide the input for climate negotiations under the UNFCCC and a consistent global energy outlook as boundary conditions for more detailed analyses of the EU energy markets and related policy areas.

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.

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.