An empirical mode decomposition-extreme learning machine (EMD-ELM) wind power prediction method based on the hierarchical clustering method was proposed to solve the current problem of insufficient power prediction accuracy of wind power stations in this paper. This method uses the aggregation algorithm of hierarchical clustering to cluster the data with similar weather conditions, and uses the EMD method to decompose the power sequence of each group, which can obtain relatively stable data components, and finally uses the ELM method to predict and combine each component. Compared with the ELM wind power prediction model, the numerical simulation shows that the EMD-ELM wind power prediction model based on hierarchical clustering method makes the data characteristics of similar weather conditions more obvious, the value of each evaluation index is better and the model has higher prediction accuracy.
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