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 paper proposes a combined prediction method based on the Markov chain to improve the precision in short-term wind power prediction. First, three chaotic models are proposed for the prediction of chaotic time series. Then, the proposed model combining these three models with weights calculated by a Markov chain is constructed. Finally, the industrial data from a Chinese wind farm is taken as a study case, and its results validate the feasibility and superiority of the proposed prediction method