Quoted from: https://www.diw.de/de/diw_01.c.599753.de/modelle.html#ab_599749 

The energy system and resource market model "MultiMod" is a large-scale representation of the supply and demand of fossil fuels and renewable energy sources. It captures in a unified framework important energy market features such as endogenous substitution between fuels, infrastructure constraints and endogenous investment, as well as market power by producers of fossil fuels.

"This model was developed within the BMBF-project RESOURCES, in collaboration with NTNU Trondheim. It is updated in the EU Horizon 2020 project SET-Nav. The mathematical formulation of the MultiMod model is a dynamic Generalized Nash Equilibrium (GNE) derived from individual players' profit maximisation problems. The formulation is generic and flexible, so that the supply chain of any number of fossil and renewable fuels can be modelled. The framework includes seasonality and allows for a detailed infrastructure representation and a comprehensive transformation sector (power generation, refinery sector). Investment in infrastructure (transportation, seasonal storage, transformation) is determined endogenously in the model according to the respective player’s inter-temporal optimisation problem. Furthermore, substitution between different energy carriers on the final demand side is endogenous. By formulating the model as an equilibrium problem with different player types based on non-cooperative game theory, the model can incorporate Cournot market power by individual suppliers as well as distinct discount rates by various players concerning their investment. The current framework is an open-loop perfect foresight model. A stochastic version of the model is under development at NTNU Trondheim. This will allow for consideration of uncertainty and distinct risk profiles for individual players along the supply chain, including investment by consumers in energy efficiency.

The model is formulated and solved as a Mixed Complementarity Problem (MCP) and implemented in GAMS, using MS Access and MS Excel for data processing and output reports. Initially, a database representing the global energy system was compiled and used for scenario analysis (Huppmann & Egging, 2014). Other datasets or variations of the initial data base are have later been developed within specific research projects:

• Focus on US domestic energy markets (oil, natural gas) (lead: Johns Hopkins University)
• Focus on the global crude oil market and refinery investment (lead: DIW Berlin)Focus on global natural gas markets (lead: DIW Berlin), used in the Energy Modeling Forum Round 31 (EMF31) on "North American Natural Gas and Energy Markets in Transition". (link: https://emf.stanford.edu/projects/emf-31-north-american-natural-gas-and-energy-markets-transition)
• Focus on global fossil fuel markets (lead: DIW Berlin), used in the SET-Nav project