Electric vehicle charging load clustering prediction method based on generative adversarial network

The invention discloses an electric vehicle charging load clustering prediction method based on a generative adversarial network, and the method comprises the following steps: (1) obtaining electric vehicle charging samples, which are divided into workdays and non-workdays; (2) carrying out clustering analysis on the electric vehicle charging samples on workdays and non-workdays, and dividing the samples into a plurality of classes; (3) calculating the daily charging load of each class after classification in the workday and the non-workday, and obtaining historical charging load data of each class in multiple days; (4) respectively sending various historical data, weather information and noise vectors into the generative adversarial network; (5) training through the generative adversarial network to obtain a predicted value of the charging load of the electric vehicle; according to the method, the problem of insufficient samples of the traditional artificial neural network is solved, and the generalization a