Impacts of Energy Sector Integration on Power System Operation

Electrification of energy intensive sectors is one of the main tools in decreasing fossil fuel consumption and lowering emissions as the carbon intensity of electricity generation is decreasing with increased penetration of renewables in the power system. However, the change does not come without challenges as simultaneously the share of flexible power generation is declining. The flexibility required by the power system has to be sought to an increasing extent from new resources, including the demand side. Sector integration is seen as a key solution in enabling the necessary flexibility to the power system as new technologies and energy carriers could be utilised to manage fluctuations in the power system. In this thesis, power market modelling is used to illustrate and analyse the behaviour of sector integration technologies in 2035 with significantly increased electricity demand and renewable generation capacities. The focus is on technologies used in district heating and hydrogen production, namely heat pumps, electric boilers, and electrolysers. In the literature review, operation of the technologies is analysed based on existing installations and findings from pilot projects. The findings are used to discuss the potential drawbacks of current modelling methods for relevant technologies. Five modelling cases for district heating electrification and two modelling cases for hydrogen production are made to compare and analyse the impacts with different development paths of sector integration. Additionally, new demand profiles are developed for district heating heat pumps and electric boilers to better reflect their operation. The market modelling demonstrated that higher flexibility for sector integration technologies leads to higher demand changes between market hours. Higher hourly changes means that the technologies can aid the system by reacting to changes in renewable generation and electricity prices with a higher degree. However, higher flexibility may also lead to higher magnitude errors in demand forecasts used in system operation which can have significant impacts on system operation activities