Abstract
With the popularization of electric vehicles (EVs), more and more charging stations are deployed in the urban area. This brings practical interest to the operation optimization of the charging station in a competitive charging market. As EV drivers are sensitive to the charging cost, the charging price is one of the major concerns during the operation optimization for the charging station. This paper considers this important problem and makes the following contributions. Firstly, a charging demand simulation method is proposed to generate the potential charging demand based on the transportation network and EV trip characteristic. By multiple scenarios generation, the uncertainties in the charging demand can be incorporated. Secondly, a competitor awareness model is proposed to predict the possible charging pricing policies of the competitors. This method can discover the implicit relationship between pricing policy and the status of the competitors without the requirement of the competitors’ utility functions. Thirdly, a Grey wolf optimization (GWO)-based charging price determination algorithm is proposed considering the uncertain charging demand, the pricing policies of the competitors and the charging willingness of EVs. Numerical results demonstrate that the proposed method can improve the competitiveness and the operation profit of the charging station.
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Funding
This work was supported by Science and Technology Project of State Grid Jiangsu Electric Power Co., Ltd. (Grant No. J2023012).
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Fei Zeng contributed to conceptualization and methodology. Xiaodong Yuan contributed to supervision and project administration. Yi Pan contributed to software and writing. Mingshen Wang contributed to methodology and writing. Huiyu Miao contributed to resources and suggestion. Huachun Han contributed to revision and suggestion. Shukang Lyu contributed to revision and suggestion.
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Zeng, F., Yuan, X., Pan, Y. et al. GWO-based charging price determination for charging station with competitor awareness. Electr Eng (2024). https://doi.org/10.1007/s00202-024-02461-1
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DOI: https://doi.org/10.1007/s00202-024-02461-1