Dynamic Pricing and Control for EV Charging Stations with Solar Generation

Hernandez Cedillo, Monica; Sun, Hongjian; Jiang, Jing; Cao, Yue

Abstract

Demand response is one of the most promising tools for smart grids to integrate more renewable energy sources. One critical challenge to overcome is how to establish pricing and control strategies for integrating more electric vehicles (EVs) and renewable energy sources. This paper proposes a dynamic optimal operation of a solar-powered EV charging station where onsite solar generation, number of EVs in the system, historical EV response to price, EV technical specifications and EV driving behaviour vary. A bi-level optimisation approach is proposed, where pricing tariffs ensure an economic and price responsive operation, then EV charging schedules are computed for energy bidding capacity to provide balancing services. Simulations are conduced to evaluate the performance of unidirectional and bidirectional EV charging at different charging speeds and demand elasticity. Results demonstrate the potential of extra revenue streams coming from the participation in energy markets compared to that of EV charging alone. Additionally, limitations of energy bidding with battery size, trip requirements and charging ratings are discussed to show insights into the operation of charging stations.

Citation

Hernandez Cedillo, M., Sun, H., Jiang, J., & Cao, Y. (2022). Dynamic Pricing and Control for EV Charging Stations with Solar Generation. Applied Energy, 326, Article 119920. https://doi.org/10.1016/j.apenergy.2022.119920

• Journal Article Type: Article
• Acceptance Date: Aug 30, 2022
• Online Publication Date: Sep 14, 2022
• Publication Date: Nov 15, 2022
• Deposit Date: Sep 5, 2022
• Publicly Available Date: Oct 12, 2022
• Journal: Applied Energy
• Print ISSN: 0306-2619
• Electronic ISSN: 1872-9118
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 326
• Article Number: 119920
• DOI: https://doi.org/10.1016/j.apenergy.2022.119920
• Public URL: https://durham-repository.worktribe.com/output/1195613