The transition process of the energy sector towards climate neutrality requires profound changes in various dimensions. A central element for the achievement of climate neutrality is the complete decarbonisation of the power system by a large-scale integration of renewables, combined with additional electrification of energy demands, notably in the heat and transport sectors. This approach is commonly denoted as “sector coupling”. The associated restructuring of energy usage entails the urgent need of investment in new technologies, if current climate protection targets are to be met. The resulting growth of electricity demand does not only result in a need for new electricity generation assets, but also leads to new challenges in decision-making on the optimal usage of sector coupling technologies, both regarding investment decisions and day-to-day operation. This dissertation aims to move these challenges and methodologies to the centre of attention to enhance decision-making for asset portfolios, with a dedicated focus on combined heat and power portfolios operating in district heating grids. It consists of four individual contributions, which investigate the complex multi-market participation opportunites that arise for power plant owners. As there is a significant uncertainty regarding relevant parameters when such decisions are made, there is a need for tools and methods that allow for an accurate depiction of this uncertainty. A central method for (energy system) optimisation under uncertainty is stochastic optimisation, whose applicability and performance is therefore investigated by a majority of the contributions included in this dissertation.
Christian Furtwängler (Wed,) studied this question.