Short-term photovoltaic prediction by using H filtering and clustering

Yasuhiko Hosoda, Toru Namerikawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)


This paper deals with prediction algorithm applying for photovoltaic (PV) systems in smart grid. This prediction is aim to predict the amount of the next day of generation using the previous data and the weather forecast which get from Japan Meteorological Agency. The procedure of prediction consists of two steps, the data processing and the unknown parameters estimation. In the data processing, our proposed method considers the characteristics of PV generation using cluster ensemble. We propose the cluster ensemble based on k-means to choose the groups with a correlation with previous data. In the unknown parameters estimation, we provide the regression model for PV generation and the unknown parameters are estimated via H filtering. The effectiveness of the proposed prediction method is demonstrated through numerical simulations.

Original languageEnglish
Title of host publication2012 Proceedings of SICE Annual Conference, SICE 2012
PublisherSociety of Instrument and Control Engineers (SICE)
Number of pages6
ISBN (Print)9781467322591
Publication statusPublished - 2012 Jan 1
Event2012 51st Annual Conference on of the Society of Instrument and Control Engineers of Japan, SICE 2012 - Akita, Japan
Duration: 2012 Aug 202012 Aug 23

Publication series

NameProceedings of the SICE Annual Conference


Other2012 51st Annual Conference on of the Society of Instrument and Control Engineers of Japan, SICE 2012


  • Clustering
  • Estimation
  • PV
  • Prediction
  • Short-term
  • Smart Grid
  • k-means

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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