Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.781481
Title: Characterisation and optimisation of energy storage installations for low voltage networks and EV chargers
Author: Hilton, George
ISNI:       0000 0004 7967 1041
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2019
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Abstract:
Energy storage has been widely suggested as an enabling technology to aid society's transition to zero carbon emissions. This thesis focuses on two of the locations in which energy storage can be installed to aid this transition. Energy storage installations in high rate electric vehicle chargers are also examined in this thesis. To inform this work, a model for predicting the power demand at high rate chargers was produced. This model is based on open source, freely available data and can be used for any location on the strategic road network in the UK. Using this model paired with solar energy generation patterns, it was found that ,energy storage is able to balance the load and supply in the day scale for a high rate charger powered by renewable energy. However, for longer durations, a grid connection is nec­essary due to the seasonal changes inherent in solar power generation. A model of a high rate electric vehicle charger is also presented in this thesis. This was used to examine the different potential use cases for a high rate EV charger with an associated off-vehicle energy store and solar PV generation. Additionally, the optimal design of such a system is presented in this thesis for various future scenarios. This shows that the inclusion of energy storage at high rate EV chargers is both technically and financially sensible when the price of the grid connection is high and the EV fleet grows at a high rate. The efficacy of batteries installed on the low voltage feeder network are then compared to domestic batteries. It was seen that feeder connected batteries are better able to respond to changes in the feeder load patterns, leading to more desirable outcomes.
Supervisor: Cruden, Andrew Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.781481  DOI: Not available
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