PDF(3670 KB)
Optimal Charging and Discharging Strategies for Electric Vehicle Clusters Considering Power Peak Shaving
ZHAO Linxin, LI Chengxin, GUI Jiangyi, LIU Lin
Electric Power Construction ›› 2025, Vol. 46 ›› Issue (11) : 24-34.
PDF(3670 KB)
PDF(3670 KB)
Optimal Charging and Discharging Strategies for Electric Vehicle Clusters Considering Power Peak Shaving
[Objective] In a source-grid-load-storage system incorporating renewable energy， an electric vehicle （EV） cluster charging and discharging strategy optimization model is established to optimize the revenues of EV users and load aggregators participating in peak-shaving ancillary services， considering the peak-shaving demand levels across different time periods.[Methods] First， the peak-shaving demand for each time period under renewable energy production scenarios was assessed. Second， based on the level of the peak-shaving demand in each time period， an optimization model for the charging and discharging strategy of the EV cluster was developed to maximize the total expected revenue for both load aggregators and EV users. Finally， to prevent peak load occurrences after participating in peak-shaving services， the charging and discharging strategy for subsequent time periods were optimized to minimize load fluctuations.[Results] The case analysis demonstrated that the proposed charging and discharging strategy assisted in smoothing the electricity load during peak periods， maximized the total expected revenue for load aggregators and EV users， and mitigated the occurrence of load peaks after participating in peak-shaving services.[Conclusions] The strategy proposed in this study significantly improved the benefits for EV users and load aggregators compared with the strategy without considering participation in the peak-shaving service， and the load fluctuations in the subsequent period of peak shaving were significantly reduced that verified the practicality and effectiveness of the proposed method.
source-grid-load-storage system / electric vehicle （EV） users / load aggregators / peak-shaving ancillary services / EV cluster charging and discharging strategy optimization / load peaks
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