National Energy System Model with Focus on Intersectoral System Development



Study | Fraunhofer ISE | Februar 2020

Paths to a Climate-Neutral Energy System

The German Energy Transition in its Social Context

© Fraunhofer ISE
Scheme of the energy system as presented in the simulation model of REMod.

Focus of analysis

  • Cost-optimized structural developments of greenhouse gas neutral national energy systems
  • Future year-specific expansion paths of technologies as well as market share and technology trends
  • Technology-specific operation management strategies based on the interaction of sector-coupled technologies
  • Impact and meaningfulness of sector-coupling technologies such as electric vehicles, electrolysers, or electric heat pumps in the overall system context

Background of model application

In order to achieve the set climate protection goals, the German government has decided to fundamentally restructure the energy system. A fundamental transformation of the current energy system is thus inevitable. How and with which effects this restructuring takes place is the subject of the analyses with the energy system model REMod:

How can a cost-optimal transformation of a national energy system - taking into account all energy sources and consumer sectors - be achieved in line with the declared climate goals and the guarantee of a secure energy supply? Due to the customizable execution of scenario-based simulations, the REMod model is ideally suited to answer specific questions regarding the transformation of national energy systems. In repeated cooperation with federal and state ministries, international research institutions and especially through close exchange with industrial customers, the applicability as a strategic consulting tool has been proven and the model has been continuously developed.  

Characteristics of the model

The functionality of the REMod model is based on a (non-linear) cost optimization of national energy supply systems whose energy-related CO2-emissions do not exceed a given target value and/or target path. The optimization objective is to scale all generators, storage facilities, converters, and loads at minimum cost such that the overall system energy balance is met at every hour. Each technology property can be mapped in any level of detail. For example, different charging strategies for battery-electric vehicles or the interaction of thermal storage and different heating systems can be mapped realistically. Thus, in addition to ecological sustainability and economic efficiency, the model also takes into account security of supply through a high level of technical detail as well as temporal resolution that reconciles energy demand and supply at every hour throughout the year. Similarly, a multi-node approach allows different regions in the observation area to be mapped and their interaction with each other to be investigated, enabling conclusions to be drawn about infrastructure measures.

The following characteristics describe the REMod model

  • Technical focus: description of the interaction of the energy sectors electricity, heat, mobility and industry on the transformation path until 2045
  • Goal: Determine the cost-optimal transformation of the German energy system by 2045 and achieve the defined reduction of greenhouse gas emissions.
  • Energy system model type: technical, bottom-up energy system model with dynamic, non-linear optimization of expansion planning.
  • Geographic coverage: national (e.g., Germany) and regional possible (e.g., states)
  • Temporal resolution: hourly from 2020 (calibration) to 2050
  • All sectors: Demand, generation, storage, energy conversion, demand-side management, and infrastructures
  • Framework: Compliance with a specified reduction in greenhouse gas emissions (budget and/or annualized)
  • Dealing with uncertainty: sensitivity analyses e.g. different scenario calculations
  • Programming language: julia / Python, Solver: Covariance Matrix Adaptation Evolution Strategy (CMA-ES)


  • Energy service providers
  • Industry
  • Political decision makers
  • Public institutions