Husarek, Dominik (2023)
Analysis of sector-coupling effects between the mobility sector and the energy system under consideration of energy transport and charging infrastructure.
Technische Universität Darmstadt
doi: 10.26083/tuprints-00023140
Ph.D. Thesis, Primary publication, Publisher's Version
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Item Type: | Ph.D. Thesis | ||||
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Type of entry: | Primary publication | ||||
Title: | Analysis of sector-coupling effects between the mobility sector and the energy system under consideration of energy transport and charging infrastructure | ||||
Language: | English | ||||
Referees: | Niessen, Prof. Dr. Stefan ; Steinke, Prof. Dr. Florian | ||||
Date: | 2023 | ||||
Place of Publication: | Darmstadt | ||||
Collation: | xii, 149 Seiten | ||||
Date of oral examination: | 11 November 2022 | ||||
DOI: | 10.26083/tuprints-00023140 | ||||
Abstract: | Within the next decades, energy systems must be decarbonized and rely on renewable energy sources in the electricity, heat, and mobility sectors. This requires sector-coupling technologies such as electrolyzers, heat pumps, or charging infrastructure for electric vehicles. Additionally, energy transport networks for electricity and gas, including hydrogen, must be expanded. To design future energy systems cost-efficiently, those sectors and the energy transport infrastructure can no longer be considered independently but require an integrated assessment approach. While the decarbonization of Germany's electricity and heat sectors has progressed since 1990, the emissions in the mobility sector stagnate. The decarbonization of the mobility sector requires new powertrain technologies and energy infrastructure enabling the utilization of electricity, hydrogen, or electricity-based fuels. Especially a carbon-neutral hydrogen supply chain and the charging infrastructure for battery electric vehicles are new, disruptive elements in the energy system. Electrolyzers, hydrogen storage, and the corresponding transport infrastructure couple the mobility sector indirectly with the electricity sector. This affects the electricity demand and provides flexibility for intermittent renewable energy sources. Charging stations couple the mobility sector directly with the electricity sector. The upcoming electrical charging demand is driven by electric vehicle drivers' heterogenous driving and charging behavior, which can differ significantly from conventional refueling behavior today. In the present thesis, a model framework is developed and applied to analyze the interdependencies of a decarbonized mobility sector and the energy supply, energy transport, and charging infrastructure of a carbon-neutral, multi-modal energy system. The analysis aims at assessing cost-optimal energy carriers in the mobility sector and the correspondingly required renewable energy sources, energy imports, storage capacities, and transport infrastructure for electricity and hydrogen in Germany. Further, it aims at assessing the required charging infrastructure for battery electric vehicles, including slow and fast charging technologies at various locations. The impact of differently designed charging infrastructure networks on the multi-modal energy system is analyzed regarding the electricity charging peak load and the available flexibility from controlled charging processes. The developed framework consists of a mathematical energy system optimization model and an agent-based electric vehicle simulation. The energy system model is parametrized to optimally design a carbon-neutral German multi-modal energy system in 2045 with its energy supply, transport, and demand infrastructure. It considers 38 administrative areas in Germany and 13 energy exchange countries in Europe. A scenario-based local sensitivity analysis is applied to assess the impact of different energy carriers in the mobility sector on the multi-modal energy system and to assess the cost-optimal energy carriers in the mobility sector under consideration of different energy supply and transport scenarios. The agent-based simulation focuses on the charging and driving behavior of battery electric passenger vehicles. It is applied to identify Pareto optimal charging infrastructure network designs for rural and urban areas. The output is used to parametrize the charging infrastructure and electric vehicle charging demand time series in the energy system optimization model. A sensitivity analysis is applied by varying the availability of slow and fast charging stations at different locations in an urban and a rural area to assess the impact of different charging infrastructure network designs on the electricity charging peak load and the available flexibility from electric vehicle charging. The analysis in the energy system model shows that efforts to enable a high electrification rate in the mobility sector can be considered no-regret measures. However, uncertainties in the availability and costs of energy supply and transport infrastructure primarily affect the cost-optimal electrification rate of capital-intensive technologies such as heavy-duty vehicles and buses. While electricity-based fuels are mainly consumed by heavy-duty vehicles, busses, ships, and airplanes, hydrogen can cost-optimally complement the electrification of light-duty vehicles and passenger cars. Both generation of hydrogen and electricity-based fuels can be cost-competitive at locations with large wind power generation in Germany, with electrolyzers operating in hours with low marginal electricity costs, compared to international locations. If hydrogen is used directly in the mobility sector, the required hydrogen transport infrastructure must be expanded from connecting only hydrogen generation and import regions with industrial demand regions towards a country-wide coverage. Furthermore, the results show that each 10%-increase of the electrification rate in the mobility sector requires an additional stationary energy storage capacity of 250 GWh, including thermal storage, hydrogen storage, and battery storage. However, the required battery storage capacity can be reduced by up to 45 GWh by controlled charging of electric passenger vehicle fleets. The charging infrastructure network design significantly affects the volume of dispatched flexibility from battery electric vehicles and, correspondingly, the required battery storage capacity within the energy system. Fostering a dense network of fast chargers can significantly reduce the required number of slow chargers in the initial market phase of electric vehicles. With a growing number of electric vehicles, the design of regional charging infrastructure networks can be used increasingly effectively to reduce the electricity charging peak load and increase the available flexibility of a fleet of electric vehicles. This thesis contributes to the research on decarbonized energy systems and shows the need for an integrated design process for future energy systems. It additionally reveals the relevance of comprehensively designing charging infrastructure networks for battery electric vehicles by quantifying the impact of different charging infrastructure networks on the charging peak load, on the available flexibility of charging processes, and on a fully multi-modal energy system. |
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Uncontrolled Keywords: | Energy system modelling, electric vehicle charging infrastructure, agent-based modelling, decarbonization, hydrogen | ||||
Status: | Publisher's Version | ||||
URN: | urn:nbn:de:tuda-tuprints-231401 | ||||
Classification DDC: | 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering | ||||
Divisions: | 18 Department of Electrical Engineering and Information Technology > Technology and Economics of Multimodal Energy Systems (MMES) | ||||
Date Deposited: | 15 Feb 2023 13:06 | ||||
Last Modified: | 17 Feb 2023 09:55 | ||||
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/23140 | ||||
PPN: | 505070006 | ||||
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