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

Tomoki Ishikawa, Takaaki Kojima, Toru Namerikawa

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)81-89
Number of pages9
JournalIEEJ Transactions on Electronics, Information and Systems
Volume135
Issue number1
DOIs
Publication statusPublished - 2015 Jan 1

Keywords

  • Constrained kalman filter
  • Energy management systems (EMS)
  • JIT modeling
  • Short-term prediction
  • Wind power

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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