Genetic Algorithm Optimizing Neural Network for Short-Term Load Forecasting

Author

Wu, Wang ; Guozhi, Wang ; Yuanmin, Zhang ; Hongling, Wang

Author_Institution

Electro-Inf. Coll., Xuchang Univ., Xuchang, China

Volume

1

fYear

2009

fDate

15-17 May 2009

Firstpage

583

Lastpage

585

Abstract

Short-term load forecasting in power system is necessary for management and control of power system. A new method for short-term load forecasting was presented based on neural networks optimized by genetic algorithm (GA) is proposed in this paper, short-term load forecasting model for power system was setup as sample sets for Elman neural network (Elman NN), with GA´s optimizing and Elman NN´s dynamic feature, the higher forecasting pricision was realized and the simulation indicates the method is feasible and effective.

Keywords

genetic algorithms; load forecasting; neural nets; power engineering computing; power system control; power system management; Elman neural network; genetic algorithm; optimization; power system control; power system management; short-term load forecasting; Genetic algorithms; Load forecasting; Neural networks; Optimization methods; Power system control; Power system dynamics; Power system management; Power system modeling; Power systems; Predictive models; Genetic Algorithm; Neural Network; Power System; Short-Term Load Forecasting;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology and Applications, 2009. IFITA '09. International Forum on

Conference_Location

Chengdu

Print_ISBN

978-0-7695-3600-2

Type

conf

DOI

10.1109/IFITA.2009.326

Filename

5231703