Title: Load forecasting using artificial intelligence techniques: a literature survey

Authors: R.C. Bansal, J.C. Pandey

Addresses: Electrical and Electronics Engineering Department, Birla Institute of Technology and Science, Pilani, 333031, Rajasthan, India. ' Electrical and Electronics Engineering Department, Birla Institute of Technology and Science, Pilani, 333031, Rajasthan, India

Abstract: The forecasting of electricity demand has become one of the major research fields in electrical engineering. In recent years, much research has been carried out on the application of artificial intelligence techniques to the load-forecasting problem. Various artificial intelligence (AI) techniques used for load forecasting are expert systems, fuzzy, genetic algorithm, artificial neural network (ANN), etc. This paper presents an extensive bibliography of more than 265 papers on load forecasting during over past 25 years.

Keywords: artificial intelligence techniques; artificial neural networks; expert systems; fuzzy set theory; load forecasting; short-term load forecasting; electricity demand; demand forecasting; fuzzy logic; genetic algorithms; literature review.

DOI: 10.1504/IJCAT.2005.006942

International Journal of Computer Applications in Technology, 2005 Vol.22 No.2/3, pp.109 - 119

Published online: 26 Apr 2005 *

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