Low-carbon transformation of the German and European electricity systems
This dissertation addresses the low-carbon transformation of the German and European electricity sectors. It applies techno-economic electricity sector models to research questions on market design and infrastructure investment. The first part consists of three chapters on Germany. It starts with a chapter on the nodal dispatch model for the German electricity system (ELMOD-DE) which implements the DC load flow approach. In March 2016, the respective model source code and a nodal and hourly dataset for 2012 were published to support the effort of increasing transparency in policy-oriented energy sector modeling. In the following chapter, ELMOD-DE is applied to analyze the effects of one northern and one southern bidding zone on the German electricity market. The results discuss the effect on re-dispatch levels, deviations in zonal prices, and distributional effects. The third chapter extends ELMOD-DE to a mixed-integer linear program (MILP) to determine nodal investment for renewable integration in gas-fired power stations, in pumped-storage hydroelectric plants, and in HVAC and HVDC transmission lines for the years 2024 and 2034. The second part consists of three chapters on transmission investment. It starts with a chapter on national-strategic decisions on network expansion. A game theory model determines stable expansion strategies, the effect of cost-allocation schemes, and changes in national welfare levels as results of cross-border transmission investment. The following chapter raises the issue of dynamic changes in network congestion during the low-carbon transformation. It applies a mathematical problem with equilibrium constraints (MPEC) to test different regulatory approaches and their effect on network investment. The last chapter, again, uses a MILP to determine network investment for the European transmission network up to 2050.The nodal model optimizes investments in HVDC lines and in the existing HVAC network for three different scenarios, comparing the results to the Roadmap 2050.
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