Optimal fuzzy inference for short-term load forecasting

Author

Mori, Hiroyuki ; Kobayashi, Hidenori

Author_Institution

Dept. of Electr. Eng., Meiji Univ., Kawasaki, Japan

fYear

1995

fDate

7-12 May 1995

Firstpage

312

Lastpage

318

Abstract

This paper proposes an optimal fuzzy inference method for short-term load forecasting. The proposed method constructs an optimal structure of the simplified fuzzy inference that minimizes model errors and the number of the membership functions to grasp nonlinear behavior of power system short-term loads. The model is identified by simulated annealing and the steepest descent method. The proposed method is demonstrated in examples

Keywords

fuzzy systems; inference mechanisms; load forecasting; nonlinear systems; simulated annealing; membership functions minimisation; model errors minimisation; nonlinear approximation; nonlinear behavior; optimal fuzzy inference; optimal structure; power system short-term loads; short-term load forecasting; simulated annealing; steepest descent method; supervised learning; Artificial neural networks; Fuzzy systems; Load forecasting; Power system modeling; Power system security; Power system simulation; Predictive models; Simulated annealing; Stochastic processes; Weather forecasting;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Industry Computer Application Conference, 1995. Conference Proceedings., 1995 IEEE

Conference_Location

Salt Lake City, UT

Print_ISBN

0-7803-2663-6

Type

conf

DOI

10.1109/PICA.1995.515200

Filename

515200

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2372964