Home | english  | Impressum | Datenschutz | Sitemap | KIT

Opportunities of Power-to-Gas-to-Power through smart multiple use optimization

Opportunities of Power-to-Gas-to-Power through smart multiple use optimization
Typ:Bachelorarbeit, Masterarbeit

Frederik vom Scheidt

In the future Power-to-gas is expected to play a key role in the electricity sector. An electrolyzer can use grid electricity to convert water to hydrogen and oxygen (Power-to-Gas, P2G). Modern electrolyzers can reverse that process to generate electricity and feed it back into the grid (Gas-to-Power, G2P). In combination, a Power-to-Gas-to-Power plant (P2G2P) is able to trade electricity on wholesale markets. Thanks to the technical flexibility of a P2G2P plant, it can provide multiple services to the electricity system.
Past studies have only analyzed how profitable P2G2P is with a single revenue source, like short-term energy shifting. Usually this is not profitable in most electricity markets. In this thesis the respective student is to investigate how profitability is affected when the operation of P2G2P is optimized in respect to multiple revenue opportunities, including short and long term energy-shifting and ancillary services.
Scope of thesis

The goal is to determine if P2G2P could be financially viable if several revenue opportunities are combined in a smart way. For this, the student can build on an existing basic Python model and extend it.
If the topic is taken on as a master thesis the student should additionally a) explore how changes to the current German market structure would impact profitability and b) from those findings derive relevant policy recommendations.
The thesis can be written in English or German. It can be started immediately.
Interest in energy economics and wholesale electricity markets
Basic knowledge of Python
Either good knowledge of Python or high motivation to acquire it

  • Walker, Sean B.; van Lanen, Daniel; Fowler, Michael; Mukherjee, Ushnik (2016): Economic analysis with respect to Power-to-Gas energy storage with consideration of various market mechanisms. In: International Journal of Hydrogen Energy 41 (19), S. 7754–7765. DOI: 10.1016/j.ijhydene.2015.12.214.
  • Moreno, Rodrigo; Moreira, Roberto; Strbac, Goran (2015): A MILP model for optimising multi-service portfolios of distributed energy storage. In: Applied Energy 137, S. 554–566. DOI: 10.1016/j.apenergy.2014.08.080.
  • Zhai, Qiwei; Meng, Ke; Dong, Zhao Yang; Ma, Jin (2017): Modeling and Analysis of Lithium Battery Operations in Spot and Frequency Regulation Service Markets in Australia Electricity Market. In: IEEE Trans. Ind. Inf. 13 (5), S. 2576–2586. DOI: 10.1109/TII.2017.2677969.