A multi-time-scale considering multi-type energy storage collaborative scheduling method

Abstract

The application discloses a multi-type energy storage collaborative scheduling method considering multiple time scales. The method comprises the following steps: S1, counting each energy storage type in a transformer area, and respectively acquiring historical output data of each energy storage type; S2, fitting correlation coefficients of each environmental data and output data according to the historical output data; predicting the all-day output change of each type of energy storage based on the estimated environmental data, and dividing time periods according to the predicted all-day output change of the energy storage; S4, formulating a collaborative scheduling plan of the multi-type energy storage based on the cumulative energy storage, the current energy storage output and the predicted energy storage output of the next time period according to the demand of the current time period; S5, performing the collaborative scheduling of the multi-type energy storage; recording feedback environmental data and energy storage output data, and optimizing the correlation coefficients. The collaborative scheduling plan is formulated according to the energy storage output characteristics of different time periods, so that the collaborative scheduling of the multi-type energy storage in multiple time periods is more accurate.