| Issue |
E3S Web Conf.
Volume 194, 2020
2020 5th International Conference on Advances in Energy and Environment Research (ICAEER 2020)
|
|
|---|---|---|
| Article Number | 03024 | |
| Number of page(s) | 6 | |
| Section | Power Engineering and Power Generation Technology | |
| DOI | https://doi.org/10.1051/e3sconf/202019403024 | |
| Published online | 15 October 2020 | |
Demand contracting strategy for charging stations based on load forecasting
1 States Grid Shanghai Municipal Electric Power Company, 200120, Shanghai, China
2 Shanghai Jiao Tong University, 200240, Shanghai, China
* Corresponding author: liuzeyu@sjtu.edu.cn
Since the stochasticity of the charging of electric vehicles (EVs) may bring impact to the grid, there is a high possibility that the demand charge will be applied to charging stations. Therefore, a load-forecasting-based demand contracting strategy is proposed for charge stations in this paper. A stochastic optimization model is established by regarding the maximal demand as a stochastic parameter, and the object of the model is to minimize the expectation of demand charge, and the analytic solution is derived. To obtain the distribution of actual maximal demand, a Monte-Carlo-based charge load forecasting method is proposed. It gives the distribution of the daily maximal demand, based on which the distribution of monthly maximal demand is also derived. The case study illustrates the feasibility and the validity of the proposed strategy.
© The Authors, published by EDP Sciences, 2020
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