A comprehensive day-ahead scheduling strategy for electric vehicles operation. (October 2021)

• Record Type: Journal Article
• Authors: Tookanlou, Mahsa Bagheri; Ali Pourmousavi Kani, S.; Marzband, Mousa
• Is Part Of: International journal of electrical power & energy systems. Volume 131(2021)
• Publication Date: 2021-10
• Subjects: Charging and discharging strategy -- Cloud scheduling system -- Electricity pricing -- Electric vehicles -- Three-layer optimisation problem; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2021.106912
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Optimal simultaneous operation of electric vehicles, charging stations and retailers. Charging stations are selected based on shortest routes and cost/benefit of services. Charging stations select retailers from wholesale market to maximise their profit. Day-ahead prices are determined for all stakeholders during charging and discharging 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.