AUTHOR=Zhou Liangsong , Zhou Xiaotian , Liang Hao , Huang Mutao , Li Yi TITLE=Hybrid Short-Term Wind Power Prediction Based on Markov Chain JOURNAL=Frontiers in Energy Research VOLUME=Volume 10 - 2022 YEAR=2022 URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.899692 DOI=10.3389/fenrg.2022.899692 ISSN=2296-598X 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.