Short-term wind power prediction for wind turbine via kalman filter based on JIT modeling

Tomoki Ishikawa, Takaaki Kojima, Toru Namerikawa

研究成果: Article査読

1 被引用数 (Scopus)


This paper addresses wind power prediction which is known to be a key technology in EMS(Energy Management Systems). In this paper, 24 hours ahead power prediction method using a filtering theory is proposed for wind power generation. The prediction method is a simple algorithm, the procedure of prediction consists of two steps, the data processing and the calculation of predicted values. In the data processing, in order to get the correlative data from the database, we employ JIT(Just-In-Time) Modeling. In the calculation of predicted value, we propose the regression model for wind speed and wind power, and the unknown parameters are estimated via constrained kalman filter. Moreover, in a procedure of estimation of the unknown parameters, reduction and the convergence of them are also guaranteed. Finally, the advantages of the proposed method over the conventional method are shown through actual prediction evaluations.

ジャーナルIEEJ Transactions on Electronics, Information and Systems
出版ステータスPublished - 2015

ASJC Scopus subject areas

  • 電子工学および電気工学


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