DocumentCode :
3095266
Title :
Long-term electric power load forecasting using fuzzy linear regression technique
Author :
Al-Hamadi, H.M.
Author_Institution :
Dept. of Inf. Syst., Kuwait Univ., Safat, Kuwait
Volume :
3
fYear :
2011
fDate :
8-9 Sept. 2011
Firstpage :
96
Lastpage :
99
Abstract :
This paper presents a new technique for long-term electric power load forecasting. The technique is based on fuzzy linear regression which uses long term annual growth factors to estimate fuzzy linear regression model parameters. In this technique a linear optimization problem is formulated, where the objective is to minimize the spread of fuzzy regression parameters. The annual growths for each of the long-term forecasting factors are calculated using cubic polynomials. The performance of the proposed technique is illustrated on real power network data.
Keywords :
fuzzy set theory; load forecasting; optimisation; polynomial approximation; regression analysis; cubic polynomials; fuzzy linear regression model parameters; linear optimization problem; long term annual growth factors; long-term electric power load forecasting; real power network data; Autoregressive processes; Forecasting; Linear regression; Load forecasting; Load modeling; Mathematical model; Linear Fuzzy regression; Long-term load forecasting; annual growth;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering and Automation Conference (PEAM), 2011 IEEE
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-9691-4
Type :
conf
DOI :
10.1109/PEAM.2011.6135023
Filename :
6135023
Link To Document :
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