H∞ filter-based short-term electric load prediction considering characteristics of load curve

Toru Namerikawa, Yasuhiko Hosoda

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

This paper deals with H∞ filter-based short-term electric load prediction taking into consideration the characteristics of the load curve. We propose a predictive method to forecast the future electric load demand for 36 h from 12:00 PM, and evaluate the peak and bottom of the load curves on the next day. We propose a load model, estimate the unknown parameters of the model by means of an H∞ filter using the data separated for nonworking days and weekdays, with the same pattern of the previous data chosen and assigned to the model parameters. The simulation results show the effectiveness of the proposed prediction methodology.

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalElectronics and Communications in Japan
Volume97
Issue number12
DOIs
Publication statusPublished - 2014 Dec 1

Keywords

  • Characteristics of load curve
  • Electric load prediction
  • Estimation
  • Filter
  • H∞
  • Prediction

ASJC Scopus subject areas

  • Signal Processing
  • Physics and Astronomy(all)
  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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