Hernandez Cedillo, Monica, Sun, Hongjian, Jiang, Jing and Cao, Yue (2022) Dynamic Pricing and Control for EV Charging Stations with Solar Generation. Applied Energy, 326. p. 119920. ISSN 0306-2619
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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.
| Item Type: | Article |
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| Additional Information: | Funding information: The authors would like to thank CONACYT, Mexican National Council for Science and Technology for providing studenship for this research work, and also thank EA Technology for providing useful raw data from real EV charging projects. This work was supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 872172 TESTBED2 project. |
| Uncontrolled Keywords: | Smart grid, demand response, EV charging, renewable energy, optimisation |
| Subjects: | H800 Chemical, Process and Energy Engineering |
| Department: | Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering |
| Depositing User: | John Coen |
| Date Deposited: | 06 Sep 2022 10:57 |
| Last Modified: | 14 Sep 2023 03:30 |
| URI: | https://nrl.northumbria.ac.uk/id/eprint/50041 |
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