Short-term Wind Power Prediction Based on ModifiedParticle Swarm Optimization Algorithm

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Short-term Wind Power Prediction Based on ModifiedParticle Swarm Optimization Algorithm

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[1]XU Min,YUAN Jianzhou,LIU Sixin.Short-term Wind Power Prediction Based on ModifiedParticle Swarm Optimization Algorithm[J].Journal of Zhengzhou University (Engineering Science),2012,33(06):32-35.[doi:10.3969/j.issn.1671-6833.2012.06.008]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 33 Number of periods: 2012 06 Page number: 32-35 Column: Public date: 2012-11-10

Title:: Short-term Wind Power Prediction Based on ModifiedParticle Swarm Optimization Algorithm

Author(s):: XU Min; YUAN Jianzhou; LIU Sixin; 1. Information Engineering School, Nanchang University, Nanchang 330031 ,China; 2. Jiangxi An’fu Power Supply Company,An’fu 343200,China; 3.Henan Power Supply Company, Yuzhou 461670,China

Keywords:: SVM; wind power prediction ; MPSO ; precision

CLC:: TM614

DOI:: 10.3969/j.issn.1671-6833.2012.06.008

Abstract:: In view of the parameter selection problems existing in the traditional support vector machine( SVM ) model in wind power prediction,this paper puts forward a new forecasting model: with modified parti.cle swarm optimization algorithm ( MPSO ) for the optimal parameters of the SVM model, the classical PSO isa global optimization algorithm. Based on it, the modified PSO( MPSO )is proposed. Results show that theSVM model optimized by the MPSO is effective in short-term wind power prediction, and the prediction preci.sion is improved.

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