Research

Journal articles, conference papers, talks and code

Electricity transmission expansion has suffered many delays in Europe in recent decades, despite its importance for integrating renewable electricity into the energy system. A hydrogen network which reuses the existing fossil gas network would not only help supply demand for low-emission fuels, but could also help to balance variations in wind and solar energy across the continent and thus avoid power grid expansion. We pursue this idea by varying the allowed expansion of electricity and hydrogen grids in net-zero CO2 scenarios for a sector-coupled European energy system with high shares of renewables and self-sufficient supply.

Using corrective actions to overcome network loading when single lines fail has the potential to free up network capacity that is otherwise underused in preventive N-1 security strategies. We investigate the impact on renewable integration of a corrective network security strategy, whereby storage or other flexibility assets are used to correct overloading that results from line outages. In a 50-bus model of the German power system utilizing these flexibility assets, so-called network boosters (NB), we find significant cost savings for the integration of renewable energy of up to 0.

To achieve ambitious greenhouse gas emission reduction targets in time, the planning of future energy systems needs to accommodate societal preferences, e.g.~low levels of acceptance for transmission expansion or onshore wind turbines, and must also acknowledge the inherent uncertainties of technology cost projections. To date, however, many capacity expansion models lean heavily towards only minimising system cost and only studying few cost projections. Here, we address both criticisms in unison. While taking account of technology cost uncertainties, we apply methods from multi-objective optimisation to explore trade-offs in a fully renewable European electricity system between increasing system cost and extremising the use of individual technologies for generating, storing and transmitting electricity to build robust insights about what actions are viable within given cost ranges.

Teaching

Courses, seminars, and supervision

TypeClassInstitutionTerm
LectureData Science for Energy System ModellingTU BerlinWS 2223
TutorialEnergy EconomicsTU BerlinWS 2122
SeminarNew Developments in Energy MarketsTU BerlinWS 2122
SeminarEnergy InformaticsKITWS 2021
TutorialEnergy System ModellingKITSS 20
SeminarEnergy InformaticsKITWS 1920
TutorialEnergy System ModellingKITSS 19
SeminarEnergy InformaticsKITWS 1819
TutorialEnergy System ModellingKITSS 18

We are always looking for keen and enthusiastic master students to work in our group. If you’re interested in writing a thesis, please send a CV and a short personal statement via e-mail.

Open Thesis Projects

  • Currently there are no futher thesis topics available.

Ongoing Thesis Projects

  • Master: Benefits of Industry Relocation for the European Energy Transition, TUB, 2022
  • Master: Onshore wind generation in Europe: A GIS-based sensitivity analysis of future technical potential under spatial constraints, TUB, 2022

Past Thesis Projects

  • Master: Optimizing the Distributed Storage Problem using Time-Expanded Network Flow, KIT, 2020
  • Master: Power Transmission Loss Modelling in European-scale Energy System Optimisation, KIT, 2019
  • Master: Selection and Evaluation of Possible Renewable Energy Import Options for the Transport Sector, Fraunhofer ISI, 2018
  • Master: Use of Renewable Synthetic Fuels in Decarbonised Shipping and Aviation,Fraunhofer ISI, 2018