A comprehensive day-ahead scheduling strategy for electric vehicles operation

Bagheri Tookanlou, Mahsa, Ali Pourmousavi Kani, S. and Marzband, Mousa (2021) A comprehensive day-ahead scheduling strategy for electric vehicles operation. International Journal of Electrical Power & Energy Systems, 131. p. 106912. ISSN 0142-0615

[img] Text
Paper1_International Journal of Electrical Power & Energy Systems.pdf - Accepted Version
Restricted to Repository staff only until 15 April 2022.
Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0.

Download (4MB) | Request a copy
Official URL: https://doi.org/10.1016/j.ijepes.2021.106912

Abstract

Distribution networks are envisaged to host significant number of electric vehicles and potentially many charging stations in the future to provide charging as well as vehicle-2-grid services to the electric vehicle owners. The main goal of this study is to develop a comprehensive day-ahead scheduling framework to achieve an economically rewarding operation for the ecosystem of electric vehicles, charging stations and retailers using a comprehensive optimal charging/discharging strategy that accounts for the network constraints. To do so, an equilibrium problem is solved using a three-layer iterative optimisation problem for all stakeholders in the ecosystem. EV routing problem is solved based on a cost-benefit analysis rather than choosing the shortest route. The proposed method can be implemented as a cloud scheduling system that is operated by a non-profit entity, e.g., distribution system operators or distribution network service providers, whose role is to collect required information from all agents, perform the day-ahead scheduling, and ultimately communicate the results to relevant stakeholders. To evaluate the effectiveness of the proposed framework, a simulation study, including three retailers, one aggregator, nine charging stations and 600 electric vehicles, is designed based on real data from San Francisco, the USA. The simulation results show that the total cost of electric vehicles decreased by 17.6%, and the total revenue of charging stations and retailers increased by 21.1% and 22.6%, respectively, in comparison with a base case strategy.

Item Type: Article
Additional Information: Funding information: The work is funded by PGR scholarship at Northumbria University and supported by a project funded by the British Council under grant contract No: IND/CONT/GA/18–19/22.
Uncontrolled Keywords: Charging and discharging strategy, Cloud scheduling system, Electricity pricing, Electric vehicles, Three-layer optimisation problem
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Elena Carlaw
Date Deposited: 16 Apr 2021 07:53
Last Modified: 25 Oct 2021 10:00
URI: http://nrl.northumbria.ac.uk/id/eprint/45932

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics