ISSN 1000-1026
CN 32-1180/TP
  • ISSN 1000-1026
  • CN 32-1180/TP

Citation: XUE Yusheng,CHEN Ning,WANG Shumin,WEN Fushuan,LIN Zhenzhi,WANG Zhen.Review on Wind Speed Prediction Based on Spatial Correlation[J].Automation of Electric Power Systems,2017,41(10):161-169. DOI: 10.7500/AEPS20170109002 copy

Review on Wind Speed Prediction Based on Spatial Correlation

  • Received Date: January 09, 2017
    Accepted Date: March 06, 2017
    Available Online: March 28, 2017

  • Abstract:

        The state-of-the-art development of spatial correlation based wind speed prediction is reviewed. And the concepts of conditional correlation and its corresponding confidence correlation are introduced to improve traditional spatial correlation. Based on big-data thinking, a framework of integrating data-driven with causality-driven wind speed prediction is proposed. In the framework, correlation is mined from historical data for wind speed prediction. Spatial correlation is employed to import data sources for wind speed prediction to overcome the shortage of historical data in part. Furthermore, spatial correlation with long time lag can be used to predict drastic and sudden change in downstream wind speed. Finally, suggestions for future research under the proposed framework can be made with confidence. This work is supported by the State Key Program of National Natural Science Foundation of China(No. 61533010), NSFC-NRCT(Sino Thai)Cooperation Research Project(No. 51561145011)and State Grid Corporation of China.

  • Keywords:

    wind speed prediction; spatial correlation; dynamic features; offline modeling by classification; online feature matching

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