The “MInGa” model is a gas market model that formulates a mathematical description of the gas market using linear optimization. It includes all relevant producers, LNG terminals, storage facilities, and consumers of the European gas market. The supraregional gas transport is represented by the modeled long-distance pipeline network.
The model simulates the European gas market with perfect competition. The individual players are modelled with their marginal costs so that the total macroeconomic total costs can be minimised. Calculations can be performed both to examine the current situation of the infrastructure, as well as for the depiction and analysis of future developments. Holistic future scenarios can be set up through MInGa’s interaction with the energy system model ISAaR used at the FfE, enabling a changed, gas price-dependent gas demand to be simulated. This makes it possible to answer a wide range of questions in the gas industry. Some examples are:
- How well dimensioned are transmission capacities in the European gas transmission network?
- How will Germany’s role in the European network change?
- Which locations in Germany are suitable for the use of Power-to-Gas technology?
- How does gas demand change the cost of gas procurement?
To answer these diverse questions, the model’s level of detail must correspond to the varying requirements demanded by the questions. Geographical interconnections are currently modeled for Europe with aggregated transmission capacities for each market area, and for Germany by modeling each of the individual relevant long-distance pipelines. The temporal resolution is based on daily observation values over the course of one year. The origin of the primary data for mapping the infrastructure is transparent and the data largely comes from publicly accessible sources, such as ENTSO-G, the International Energy Agency (IEA), Eurostat, and national authorities.
Linear programming is used as the mathematical basis for the optimization problem. The minimization of the macroeconomic total costs is carried out under consideration of various actor-specific and system-related restrictions. A high degree of flexibility is ensured by the fact that the infrastructure stock as well as technical and economic constraints can be dynamically fed into the model for different calculation scenarios.
As a result, MInGa can be used to carry out studies on the utilisation of the gas transmission network and the cost development of gas procurement in the market areas. In this way, current issues, such as the effects of a merger of the two German market areas, can be quantified.
MInGa is being developed in the project “Dynamic and intersectoral measure assessment for the cost-efficient decarbonisation of the energy system” (Dynamis). In iterative combination with the energy system model ISAaR, repercussions of CO2 reduction measures on the gas market are to be dynamically evaluated there. In future projects, a project-specific further development of the MInGa model is aimed at in order to further improve the level of detail and informative value.
Further information and relevant publications
- EEM 2020 – WEGA and MInGa – Considering regional transmission capacities for global gas market models
- Modelling cost-efficient transformation pathways of German industry
- How does green hydrogen reach the consumer? Potential hydrogen infrastructure in Germany
- What is the National Hydrogen Strategy (NWS) and what does it entail?
- Decarbonisation in Germany – An Overview
- 15th International Conference on the European Energy Market (EEM 2018) – “The impact of electrification on the gas sector”
- 14th International Conference on the European Energy Market (EEM 2017) – “Coupling of Electricity and Gas Market Models”
- 10th International Energy Economics Conference (IEWT 2017) – “Modelling the European gas market to demonstrate different gas import scenarios”
- Dynamis – Dynamic and intersectoral policy assessment for the cost-efficient decarbonisation of the energy system
- CO2 mitigation costs of gases – development of static CO2 mitigation cost curves