Research cluster "Sector coupling und Microgrids (STROM)" – Subproject 2: Potential assessment und Model integration

Project coordination Chair of Renewable and Sustainable Energy Systems (ENS), Technical University of Munich (Prof. Dr. Thomas Hamacher)
Partners

Research partners:

  • Professorship for Cyber-Physical Systems, TU Munich (Prof. Dr.-Ing. Althoff)
  • Chair of Energy Economy and Application Technology, TU Munich (Prof. Dr.-Ing. Wagner)
  • Forschungsstelle für Energienetze und Energiespeicher (FENES), OTH Regensburg (Prof. Dr.-Ing. Brückl)
  • Professorship for Power Transmission Systems, TU Munich (Prof. Dr.-Ing. Witzmann)
  • CENERGIE – Forschungsinstitut für energieeffiziente Gebäude und Quartiere, Munich University of Applied Sciences (Prof. Dr.-Ing. Schweigler)
  • Institute of New Energy Systems (InES), Technische Hochschule Ingolstadt (Prof. Dr.-Ing. Zörner)
  • Chair of Energy Systems, TU Munich(Prof. Dr.-Ing. Spliethoff)
  • Campus Feuchtwangen: Nachhaltigkeit – Schwerpunkt Bauwesen, Hochschule für angewandte Wissenschaften Ansbach (Prof. Dr.-Ing. Nemeth)

Industry partners:

  • Thüga AG
  • Stadtwerke Augsburg
  • Energie Südbayern GmbH
  • Stadtwerke Neuburg an der Donau
Funding Bavarian Research Foundation
Duration April 2021 until September 2024
Contact M. Sc. Soner Candas

Research cluster "Sector coupling und Microgrids (STROM)"

The research association "Energy - Sector Coupling and Micro-Grids", or "STROM" for short, is developing technical, organizational, planning and regulatory solutions to rapidly advance the transformation of the energy system. The integration of electricity into the heat and mobility sectors is a necessary prerequisite for significantly increasing the share of renewable energies in these sectors. These sectors can also better store renewable energy, including from intermittent sources. Intelligent control of all resources should avoid costly grid expansion as far as possible and make optimum use of existing infrastructure. The renovation of buildings and the use of new heating technologies must be planned and implemented together. The knowledge gained will then be used in methods for the integrated planning of power and heat supply structures. The interdisciplinary research network combines expertise from mathematics, engineering and computer science in order to incorporate approaches from AI research as a cross-cutting theme in individual technology developments. The CoSESTechnikum at the Munich School of Engineering, a central research platform for research into future energy systems, makes it possible to test and prequalify technologies. The scientific work is not limited to powerto-heat technologies, energy management systems and planning tools, but also considers regulatory and economic framework conditions. The project brings together researchers from Ansbach University of Applied Sciences, Ingolstadt Technical University, Munich University of Applied Sciences, Munich Technical University and Regensburg University of Applied Sciences, as well as 26 companies from the energy sector. This connection is a necessary prerequisite for tackling the energy transition in an application-oriented and practice-oriented manner.

Subproject 2: Potential assessment and model integration

In subproject 2 "Potential assesment and model integration", led by the chair of ENS, the results of the "centralized" and "decentralized" subprojects are to be taken up and optimization models of various scales are to be brought together on a central platform in order to be able to determine the currently existing and future potential of an integrated energy supply. A characterization of heat supply areas for Bavaria as well as selected cities will also be carried out. Interactions with neighboring countries will be integrated with a superordinate modeling approach, for which mathematical approaches for model coupling will be used.

The backgroumnd of the subproject 2 can be viewed from two angles:

  • under the constant change of the power grid and here in particular the challenge to an intelligent interaction of transmission grid and distribution grid with the constant increase of renewable generators on all grid levels and an increase of the share of electricity in the final energy with new tasks in the field of mobility and heating
  • a heat turnaround and the provision of new technologies is necessary in order to make the heating sector sustainable in the long term. A new balance must be found between reducing heat demand and new generation technologies. However, the available resources must be balanced and optimally distributed.

The fulfillment of the tasks first requires an exact determination of the renewable generation potentials in Bavaria, including biomass, the building stock and refurbishment possibilities, and the electricity grids and the connection of transmission and distribution grid.
The first goal of the study is to create a Bavaria-wide heat map. The map identifies priority areas for different heat generation technologies. A first example is the work on the "Geothermie" master plan, which shows how much and where heat from deep geothermal energy could be used. Similarly, this is being extended to other technologies. It is clear that in many areas different technologies can be used in parallel. In particular, the map will not statically represent a single development, but will reflect different developments depending, for example, on the increase of electrical energy in the heat sector.
The second goal is to develop a tool for the optimal development of electricity and heat supply in regions such as urban or local districts in interaction with the overall Bavarian development and taking into account local conditions and potentials. With the help of an economic optimization, the best supply concepts will be determined.
The third goal is the development of a model coupling, which, starting from a pan-European electricity model and a Bavarian energy model, is coupled to local models for cities, districts or even streets. The central task of the coupling is to always present a consistent solution.