GRID-CLUSTERING-BASED SHORT-TERM POWER PREDICTION METHOD FOR CANYON WIND POWER

The present invention relates to the technical field of wind power prediction. Disclosed is a grid-clustering-based short-term power prediction method for canyon wind power. The method comprises the following steps: step S1, according to canyon wind power features, dividing the short-term power prediction method into a data cleaning stage, a grid decomposition stage and a power prediction stage; step S2, in the data cleaning stage, performing abnormality detection, data supplementation and correction, and smoothing processing on historical meteorological data, historical wind power data and historical wind power prediction data which are learned by means of an LSTM network, so as to acquire complete historical data; step S3, in the grid decomposition stage, performing grid clustering of a canyon wind power station area according to latitude, so as to acquire wind power, and feature grids associated with meteorology; and step S4, in the power prediction stage, performing power prediction on each grid by using