Dynamic charging of electric vehicles integrating renewable energy: a multi-objective optimisation problem

Harry Humfrey, Hongjian Sun, Jing Jiang

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)
16 Downloads (Pure)

Abstract

Dynamically charging electric vehicles (EVs) have the potential to significantly reduce range anxiety and decrease the size of battery required for acceptable range. However, with the main driver for progressing EV technology being the reduction of carbon emissions, consideration of how a dynamic charging system would impact these emissions is required. This study presents a demand-side management method for allocating resources to charge EVs dynamically considering the integration of local renewable generation. A multi-objective optimisation problem is formulated to consider individual users, an energy retailer and a regulator as players with conflicting interests. A 19% reduction in the energy drawn from the power grid is observed over the course of a 24 h period when compared with a first-come-first-served allocation method. This results in a greater reduction in CO2 emissions of 22% by considering the power grid's make-up at each time interval. Furthermore, a 42% reduction in CO2 emissions is achieved compared to a system without local renewable energy integration. By varying the weights assigned to the players’ goals, the method can reduce overall demand at peak times and produce a smoother demand profile. System fairness is shown to improve with an average Gini coefficient reduction of 4.32%.
Original languageEnglish
Pages (from-to)250-259
JournalIET Smart Grid
Volume2
Issue number2
Early online date5 Apr 2019
DOIs
Publication statusPublished - 1 Jun 2019

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