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Title: The impact of domestic electric vehicle charging on electricity networks
Author: Crozier, Constance
ISNI:       0000 0004 9348 0102
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2020
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This thesis investigates the impact that home charging of a large private fleet of electric vehicles would have on the power system. A large multi-regional travel survey dataset is used to model vehicle use and charging spatially heterogeneously, and a selection of representative network models are used to assess the impact of charging on system operation. A stochastic data-driven model is proposed to model uncontrolled charging of vehicles, and convex optimisation is used to calculate the optimal smart charging strategy. The power system is commonly broken down into the generation, transmission, and distribution systems. The operation of each of these systems will be impacted by the addition of EV charging to residential networks. A variety of objectives have been proposed for smart charging, each of which would protect the system in a different way. Existing research tends to focus on a single part of the system, and considers only the smart charging objective that most benefits that part of the system. Here, the three systems are modelled simultaneously, and a large range of smart charging objectives are investigated. The value of explicit loss minimising smart charging is quantified, compared to a simpler and more standard load flattening algorithm. These results are used to propose a novel optimisation formulation which reduces losses without requiring extensive network information. The value of bi-directional smart charging is also quantified compared to uni-directional smart charging, in order to investigate the viability of residential vehicle-to-grid. It is demonstrated that it is not possible to optimise the transmission level and distribution level systems simultaneously, and the penalty of only optimising for one is quantified. A method for finding a compromising solution between both system levels is proposed, which exploits the sections of the distribution where components are over-specified. Two specific case studies are investigated. The majority of the analysis in the thesis is based on the GB power system, however the Texas system is also presented as a comparative case study.
Supervisor: McCulloch, Malcom Sponsor: Jaguar Land Rover
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Electric vehicles ; Engineering ; Smart power grids