Jia, Zixuan (2024). Weather related modelling and optimization of electric vehicle integration in distribution networks. University of Birmingham. Ph.D.
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Jia2024PhD.pdf
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Abstract
As climate change becomes increasingly severe, the urgent need to reduce carbon emissions and the push for net-zero emission targets, this has led to the widespread promotion of electric vehicles. However, this transition also presents challenges, such as surges in energy demand, voltage fluctuations and potential threats to the power system equipment from extreme weather events. This thesis aims to systematically address these challenges and proposes approaches and solutions.
Firstly, the thesis proposes the data aggregation method in detail and analyses the real data results in comparison with the Monte Carlo simulation results. It was found that temperature has a significant effect on the driving and charging behaviour of electric vehicles, and the Monte Carlo method demonstrated efficiency and accuracy in bridging the gap between real data, providing an important tool for modelling EV data. Next, in order to reduce the network load pressure and charging cost while increasing the revenue of EV aggregators (EVAs) in providing ancillary services. Then the thesis proposes a scheduling approach to optimise the coordination of EV charging and ancillary services. The approach analyses the participation of EVs in ancillary services on weekdays and weekends, and reveals the impact of risk aversion parameters on the benefits of EVAs. In addition, this thesis evaluates the impact of temperature changes on EV driving and charging behaviours, and proposes a method to quantify the EV hosting capacity of distribution network in different temperature ranges. By integrating temperature data, the thesis reveals the changing of the network under different temperature and highlights the impact of weather factors on network. Finally, the thesis explains the impact of weather factor on power system equipment, and proposes a methodology for weather-related fragility modelling of power system equipment and EV charging point. It can obtain the fragility curves under different weather factors by adjusting the input parameters.
Overall, this thesis makes important contributions in terms of theoretical support and practical approaches. It provides insights for research and practice in related fields.
| Type of Work: | Thesis (Doctorates > Ph.D.) | |||||||||
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| Award Type: | Doctorates > Ph.D. | |||||||||
| Supervisor(s): |
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| Licence: | All rights reserved | |||||||||
| College/Faculty: | Colleges > College of Engineering & Physical Sciences | |||||||||
| School or Department: | School of Engineering, Department of Electronic, Electrical and Systems Engineering | |||||||||
| Funders: | None/not applicable | |||||||||
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering | |||||||||
| URI: | http://etheses.bham.ac.uk/id/eprint/15550 |
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