REMod-D – Renewable Energy Model

REMod-D – Germany: Intersectoral System Development


To achieve its climate protection targets, the German federal government has declared to fundamentally transform its energy system, requiring a thorough restructuring of the energy system as we know it today. This leads to the guiding question the REMod-D model addresses: How can a cost-optimized transformation of the German energy system – with consideration of all energy carriers and consumer sectors – be achieved in line with meeting the declared climate targets and ensuring a secure energy supply at all times? By running customized scenario-based simulations the REMod-D model is well-suited to answer specific questions concerning the transformation of the German energy system and therefore to provide strategy consulting to customers from politics, research or industry.

Characteristics of the model

The basic functionality of the REMod-D model is based on a cost-based optimization of a German energy supply system, whose energy-related CO2 emissions do not exceed a specified target value and/or target pathway. The optimisation target is to dimension all generators, stores, converters, and consumers at minimum costs such that the energy balance of the overall system is met in every hour. This means that besides environmental sustainability and cost-effectiveness, the model also addresses security of supply through time-resolved simulations which ensure the energy demand is met each hour throughout the entire year.

© Photo Fraunhofer ISE

Scheme of the energy system as presented in the simulation model of REMod-D.

The following characteristics describe the REMod-D model:

  • Goal: Determine the cost-optimal transformation of the German energy system until 2050 and achieve the defined reduction of greenhouse gas emissions.
  • Type of energy system model: Technical, bottom-up energy system model with dynamic optimization of expansion planning for lowest possible costs.
  • Technical focus: Description of the interaction between the energy sectors: electricity, heat, mobility and industry on the transformation path until 2050
  • Research area: Germany (considering one location in the north and one in the south)
  • Temporal resolution: Annual optimization until the year 2050, hourly intervals
  • Electricity sector: Demand, generation storage, energy conversion, demand-side-management. One node representation of the power grid
  • Framework conditions: Meeting a defined reduction of greenhouse gas emissions
  • Dealing with uncertainty: Sensitivity studies e. g. different scenario calculations
  • Programming language: Delphi/Python, Solver: Particle Swarm Optimization (PSO)


Potential users

  • Policy makers
  • Public utilities
  • Energy service providers
  • Industry