Abstract
Orderly charging of electric vehicles (EVs) can alleviate the impact of large-scale EVs on distribution network. Time of use (TOU) sharing pricing is an orderly scheduling strategy. However, the previous TOU pricing strategies overlook EVs participating in peak shaving and frequency regulation and the comprehensive profits of power grid, charging aggregator (CAs) and EVs. Thus, this paper studies the TOU pricing strategy. Firstly, the driving characteristics and load change characteristics of EVs are analyzed, and the cost-benefit model of EVs participating in peak load regulation and frequency regulation is constructed. Then, a TOU pricing model taking the minimum variance of EV load and the maximum cost-benefit of EV users and CAs as the objective function is modeling. The non-dominated sorting genetic algorithm (NSGA-II) algorithm is used to solve the peak-normal-valley period electricity price. The result shows the effectiveness of the TOU pricing strategy, the peak valley difference and volatility of load can be reduced, the expenditure of EV users will be reduced, and the income of CAs will be increased.
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