A new method to generate daily load scenario of electric vehicle charging station considering time correlation

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Abstract
Due to the influence of random factors such as travel behavior of car owners and traffic condition, the electric vehicle (EV) charging station load has strong randomness. Establishing an appropriate probability model to describe the stochastic of EV charging station load is of great significance to the safe operation analysis of distribution network. Therefore, this paper proposes the probability modeling and the scenario generation method for EV charging station load based on historical data. Firstly, the load of each period is regarded as a random variable, and the probability distribution model of each random variable is obtained by fitting historical data. Secondly, according to the analysis of load correlation, 96 periods of a day are divided into several sets of adjacent periods. Considering the correlation between different period loads in each set of adjacent periods, the Pair-copula method and the D-Vine structure is used to obtain the joint distribution model in each set of adjacent period loads is obtained. Thirdly, according to the joint distributionmodel, all sets of adjacent periods of a day and the corresponding load scenarios are obtained, and the daily load curve considering time correlation are generated. Finally, referring to the actual historical load curve data, the effectiveness of the proposed method in this paper is verified by comparing with the daily load curve, which is generated based on the independent distribution model of each period load without considering time correlation.