Hybrid Short-Term Wind Power Prediction Based on Markov Chain

TLDR: Wang et al. as discussed by the authors proposed a combined prediction method based on the Markov chain to realize precise short-term wind power predictions, which can master physical principles in wind power processes and guide long-term prediction.

Abstract: This article proposes a combined prediction method based on the Markov chain to realize precise short-term wind power predictions. First, three chaotic models are proposed for the prediction of chaotic time series, which can master physical principles in wind power processes and guide long-term prediction. Then, considering a mechanism switching between different physical models via a Markov chain, a combined model is constructed. Finally, the industrial data from a Chinese wind farm were taken as a study case, and the results validated the feasibility and superiority of the proposed prediction method.