Modeling an Integrated Energy Transformation of the Electricity Sector: An Open-source Analysis for Germany

This thesis addresses research questions and implications in the context of the German and European energy transformation and is comprised of three parts: Part I starts with a chapter providing an introduction to the topic. Chapter 2 then focuses on the topic of "sector coupling" and the technical and economic challenges of coupling electricity, heat, and transportation, in order to further transform towards a system relying on renewables instead of fossil and fissil fuels as a primary source of energy. For Germany some practical quantitative scenarios for sector coupling until 2030 and 2050 are being discussed. Part II deals with economic dispatch modeling. In Chapter 3 a five-fold approach to open science is introduced and the advantages of open energy models are being discussed. A fully open-source bottom-up electricity sector model with high spatial resolution using the Julia programming environment is then developed describing source code and a data set for Germany. Following the open approach, the entire model code and used data set are publicly available and open-source solvers like ECOS and CLP are used. The model is then benchmarked regarding runtime of building and solving against a representation in GAMS as a commercial algebraic modeling language and against Gurobi, CPLEX, and Mosek as commercial solvers. Chapter 4 examines the ongoing discussion about potential effects of introducing bidding zones in Germany. An electricity sector model with network representation is applied to analyze the system implications and the distributional effects of two bidding zones in the German electricity system in 2012 and 2015. Results show a modest decrease in cross-zonal re-dispatch levels, particularly in 2015. However, overall network congestion and re-dispatch levels increase in 2015 and also remain on a high level in case of two bidding zones. Results are very sensitive to more than two bidding zones and additional line investments, illustrating the challenge to define stable price zones in a dynamic setting. Chapter 5 investigates the impact of uncertain photovoltaic generation on unit commitment decisions. This is done for a market following the rolling planning procedure employing a large-scale stochastic electricity market model (stELMOD). A novel approach to simulate a time-adaptive intra-day photovoltaic forecast, solely based on an exponential smoothing of deviations between realized and forecast values, is presented. Generation uncertainty is then incorporated by numerous multi-stage scenario trees that account for a decreasing forecast error over time. Results show that total system costs significantly increase when uncertainty of both wind and photovoltaic generation is included by a single forecast, with more frequent starting processes of flexible plants and rather inflexible power plants mainly deployed at part-load. Including the improvement of both wind and photovoltaic forecasts, the scheduling costs can be significantly reduced. Part III shifts the focus to issues of the decentral energy transformation. In Chapter 6 the interdependencies between transmission line infrastructure and the electricity mix are being assessed. In particular, it is tested how an energy system based on 100 for example, copper plate or more constrained network topologies. A stylized model of optimal generation and storage investment and operation for the German electricity system is being developed. The few cases of transmission congestion in the results suggest that a high share of renewables can be accommodated by modest grid expansions and a large amount of short-term and long-term storage capacities. Chapter 7 deals with local electricity markets. Implications of recently proposed market designs under the current rules in the German market are tested using a simplistic equilibrium model representing heterogeneous market participants in an energy community with their respective objectives. We find that these proposed designs are financially unattractive to prosumers and consumers under the current regulatory framework and they even cause distributional effects within the community when local trade and self-consumption are exempt from taxes. Therefore, a novel market design is being introduced that allows for ownership and participation of renewable technologies for all community members. The analysis shows that this design has the potential to mitigate both distributional effects and the avoidance of system service charges, while simultaneously increasing end-user participation. The dissertation shows approaches and methodologies to overcome techno-economic challenges of the transformation towards renewable energy opening up even further research possibilities.