Wind speed prediction method and system for black start assisted by energy storage

The invention belongs to the technical field of wind power, and particularly provides a wind speed prediction method and system for energy storage assisted black start, and the method comprises the steps: obtaining a wind speed sequence; based on the decomposition layer number, utilizing a CEEMD algorithm to decompose the wind speed sequence to obtain a plurality of modal components, and combining a first recurrent neural network model to obtain a first error coefficient; reconstructing all modal components based on each first error coefficient to obtain a plurality of aggregated modal components, and combining a second recurrent neural network model to obtain a second error coefficient, so as to obtain an error sum; and selecting an aggregation mode component under the decomposition layer number corresponding to the minimum error sum from the error sums corresponding to different decomposition layer numbers as a target component, and obtaining a corresponding target wind speed component predicted value by us