Title :
A simplified fuzzy inference method with tabu search for short-term load forecasting in power systems
Author :
Mori, Hiroyuki ; Sone, Yasuyuki
Author_Institution :
Dept. of Electr. Eng., Meiji Univ., Kawasaki, Japan
Abstract :
This paper proposes a new method for short-term load forecasting in power systems. The proposed method makes use of simplified fuzzy inference that has an output variable in crisp number rather than fuzzy. The technique is quite popular for reducing computational effort. Also, it is quite acceptable to system operators in a sense that the output variable in crisp number is friendly to power system engineers although each input variable has the fuzzy membership functions. In order to construct the optimal structure of the fuzzy membership functions, it is necessary to use a combinatorial technique that determines the number and the location of the fuzzy membership functions. In this paper, tabu search is applied to determine them efficiently. As a metaheuristic approach, the technique is better than others in terms of computational effort and solution accuracy. The effectiveness of the proposed method is demonstrated for real data of utilities. A comparison is made between the proposed method and others
Keywords :
combinatorial mathematics; computational complexity; fuzzy set theory; inference mechanisms; load forecasting; optimisation; search problems; combinatorial technique; computational effort; fuzzy membership functions; metaheuristic approach; optimal structure; power systems; short-term load forecasting; simplified fuzzy inference method; solution accuracy; tabu search; Artificial neural networks; Costs; Expert systems; Fuzzy systems; Load forecasting; Power markets; Power system modeling; Power system planning; Power system security; Power systems;
Conference_Titel :
Decision and Control, 1998. Proceedings of the 37th IEEE Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
0-7803-4394-8
DOI :
10.1109/CDC.1998.761969