Below is a non-exhaustive list of the main modelling tools that have been developed and are maintained and operated by E3-Modelling. Their outputs support European policy making and decision making of governments and public entities for 30 years.
The GEM-E3 model is a multi-regional, multi-sectoral, recursive dynamic computable general equilibrium (CGE) model which provides details on the macro-economy and its interaction with the environment and the energy system. It is an empirical, large scale model, written entirely in structural form. GEM-E3 allows for a consistent comparative analysis of policy scenarios since it ensures that in all scenarios, the economic system remains in general equilibrium.
The PRIMES model is composed of a core suite of models which combine to form a large scale applied energy system model that provides detailed projections of energy demand, supply, prices and investment to the future, covering the entire energy system including emissions.
A number of satellite models complete the full energy system picture.
The PRIMES-TREMOVE transport model projects the evolution of demand for passengers and freight transport by transport mode and vehicle types/fuels/technologies. The model includes all Member States of the EU28 and is also able to provide detailed outlooks for Switzerland, Norway, Turkey, Albania, Bosnia, Montenegro, Serbia, N. Macedonia and Kosovo. The simulation horizon is until 2070, running on 5-year time steps.
PRIMES-Biomass computes the optimal use of biomass/waste resources and investment in secondary and final transformation, so as to meet a given demand of final biomass/waste energy products.
CompactPRIMES is designed as a one-shot country-specific model for single-country projections, aiming at addressing energy system planning, power generation investment, energy price forecasting (including removal of energy subsidies) and climate change mitigation policies including energy efficiency policies.
The Prometheus model is a comprehensive world energy model with innovative features: it integrates stochastic relations and so all exogenous variables – parameters are stochastic, following explicit probability distributions, including covariance. The model produces projections of energy demand by sector (industry, domestic, transport), power generation (representing about 25 technologies), RES, and hydrogen supply and use; the model puts emphasis on oil and gas resources.