DocumentCode
3447511
Title
Power Load Forecast Model of Genetic Neural Network Based on Tabu Search
Author
Mian, Xing ; Shu-ling, Wang ; Zhi-Hong, Gu ; Zhen-tao, Li
Author_Institution
North China Electr. Power Univ., Baoding
fYear
2007
fDate
23-25 May 2007
Firstpage
1903
Lastpage
1906
Abstract
The neural network has been applied to the area of power load forecast successfully, but it has such disadvantages of local optimization and slow convergence speed. A new kind of genetic neural network forecast model based on tabu search was proposed for overcoming those disadvantages. Utilizing the global optimizing ability of genetic algorithm and the memory function and ability of mountain climbing of tabu search, it defined a tabu aberrance operator and constructed a mixed genetic tabu algorithm, which can solve the above disadvantages of neural network and the premature problems of genetic algorithm, to train the weights and thresholds of neural network. Comparing with normal genetic algorithms, this genetic neural network based on tabu search achieved better forecast result.
Keywords
genetic algorithms; load forecasting; neural nets; power engineering computing; genetic algorithm; genetic neural network; global optimizing ability; local optimization; memory function; power load forecast model; slow convergence speed; tabu aberrance operator; tabu search; Artificial neural networks; Convergence; Genetic algorithms; Load forecasting; Load modeling; Mathematics; Neural networks; Predictive models; Publishing; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4244-0737-8
Electronic_ISBN
978-1-4244-0737-8
Type
conf
DOI
10.1109/ICIEA.2007.4318741
Filename
4318741
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