Achieving Low Carbon Emission for Dynamically Charging Electric Vehicles Through Renewable Energy Integration

Xiaolin Mou, Yingji Zhang, Jing Jiang, Hongjian Sun

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)
15 Downloads (Pure)

Abstract

Dynamic wireless charging for Electric Vehicles (EVs) can promote the take-up of EVs due to its potential of extending the driving range and reducing the size and cost of batteries of EVs. However, its dynamic charging demand and rigorous operation requirements may stress the power grid and increase carbon emissions. A novel adaptive dynamic wireless charging system is proposed that enables mobile EVs to be powered by renewable wind energy by taking advantages of our proposed traffic flow-based charging demand prediction programme. The aim is to cut down the system cost and carbon emissions at the same time, whilst realising fast demand prediction and supply response as well as relieving the peak demand on the power grid. Simulation results show that the proposed system can adaptively adjust the demand side energy response according to customers' welfare analysis and charging price, thereby to determine the power supply method. Moreover, due to the prioritised use of renewable energy, EV charging system requires less electricity from the power grid and thus the overall carbon emissions are reduced by 63.7%.
Original languageEnglish
Pages (from-to)118876-118888
Number of pages13
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 22 Aug 2019

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