Application of a fuzzy model for short-term load forecast with group method of data handling enhancement

Shyh Jier Huang, Kuang Rong Shih

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

In this paper, a fuzzy model with the enhancement of group method of data handling is applied for short-term load forecast of a power system. In the approach, the group method of data handling is applied to formulate a fitting function that finds the relationship between linguistic values of input and output. Suitable inputs can be thus determined such that the number of redundant inputs is reduced. Moreover, as the properties of input variables are embedded with the weighting values of output, additional efforts of adjusting parameters of fuzzy membership functions can also be saved. The salient feature of this method lies in that an unknown system can be modeled at ease with a fewer number of rules, thereby reducing the computation time. By performing the simulations through the utility data, test results demonstrate the effectiveness of the proposed method, hence solidifying the feasibility of the method for the application considered.

Original languageEnglish
Pages (from-to)631-638
Number of pages8
JournalInternational Journal of Electrical Power and Energy Systems
Volume24
Issue number8
DOIs
Publication statusPublished - 2002 Oct

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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