Real-time multi-objective optimisation for electric vehicle charging management

Ridoy Das, Yue Wang*, Krishna Busawon, Ghanim Putrus, Myriam Neaimeh

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The continuous increase in the uptake of electric vehicles and the interest to use electric vehicles to provide energy services require commercially viable business models for all involved stakeholders. It is, however, challenging to achieve the synergy among different stakeholders since their objectives are often conflicting. This work proposes a real-time multi-objective optimisation method where electric vehicle charging/discharging profile is scheduled in real-time to strike a balance among different objectives, namely electricity cost reduction, battery degradation minimisation and grid stress alleviation as well as meeting the electric vehicle user charging requirement by fulfilling the departure time. Dynamic programming is adopted due to its computational efficiency, which is suitable for real-time applications. The effectiveness of the proposed method is demonstrated using a residential case study where the house is equipped with an electric vehicle and a photovoltaic system, and is validated by experimental implementation. The results show that the proposed multi-objective optimisation algorithm achieves the set objectives to satisfy the stakeholders’ priorities and provides a profit for the electricity end-user that is double as compared to that achieved by a benchmark multi-objective algorithm. The results demonstrate the effectiveness of the proposed multi-objective method and its suitability for real-time charging/discharging scheduling.
Original languageEnglish
Article number126066
JournalJournal of Cleaner Production
Early online date23 Jan 2021
DOIs
Publication statusE-pub ahead of print - 23 Jan 2021

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