DocumentCode :
507263
Title :
To Forecast Short-Term Load in Electric Power System Based on FNN
Author :
Hu, Yueli ; Ji, Huijie ; Song, Xiaolong
Author_Institution :
Key Lab. of Adv. Display & Syst. Applic., Shanghai Univ., Shanghai, China
Volume :
6
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
474
Lastpage :
478
Abstract :
Electric power system load forecasting plays an important part in the Energy Management System (EMS), which has a great effect on the operating, controlling and planning of power system. Accurate load forecasting, especially short-term load forecasting, results in cost saving and guarantees secure operation condition in power system. Therefore, it is of great concern to develop an appropriate model to improve accuracy of load forecasting. In this paper, we employed the algorithm named fuzzy-neural network (FNN) and developed a prediction model for short-term forecasting. Experimental results demonstrate the effectiveness of the FNN model, and could be applied to short-term forecasting for better prediction.
Keywords :
electric power generation; energy management systems; fuzzy neural nets; load forecasting; power engineering computing; power system control; power system planning; prediction theory; Energy Management System; FNN; electric power system; fuzzy-neural network; power system control; power system planning; prediction model; short-term load forecasting; Control systems; Costs; Energy management; Fuzzy control; Load forecasting; Medical services; Power system management; Power system modeling; Power system planning; Predictive models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
Type :
conf
DOI :
10.1109/FSKD.2009.63
Filename :
5359897
Link To Document :
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