Optimal fuzzy inference for short-term load forecasting

被引：128

作者：

Mori, H ^{[1
]}

Kobayashi, H ^{[1
]}

机构：

[1] MEIJI UNIV,FAC ELECT ENGN,DEPT ELECT ENGN,TAMA KU,KAWASAKI,KANAGAWA 214,JAPAN

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 1996年 / 11卷 / 01期

关键词：

fuzzy inference; nonlinear approximation; simulated annealing; supervised learning; short-term load forecasting;

D O I：

10.1109/59.486123

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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 climber 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.

引用

页码：390 / 396

页数：7

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