Title :
Optimal fuzzy inference for short-term load forecasting
Author :
Mori, Hiroyuki ; Kobayashi, Hidenori
Author_Institution :
Dept. of Electr. Eng., Meiji Univ., Kawasaki, Japan
fDate :
2/1/1996 12:00:00 AM
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 set theory; inference mechanisms; load forecasting; simulated annealing; membership functions; model errors minimisation; nonlinear behavior; optimal fuzzy inference method; 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;
Journal_Title :
Power Systems, IEEE Transactions on
