DocumentCode :
3257345
Title :
A hybrid approach for short term electricity price and load forecasting
Author :
Mohapatra, Ankita ; Mallick, Manas Kumar ; Panigrahi, B.K. ; Cui, Zhihua ; Hong, Samuelson
Author_Institution :
Electr. Eng. Dept., Siksha `O´´ Anusandhan Univ., Bhubaneswar, India
fYear :
2011
fDate :
28-30 Dec. 2011
Firstpage :
1
Lastpage :
5
Abstract :
In a deregulated power industry, accurate short term load forecasting (STLF) and price forecasting (STPF) is a key issue in daily power market. The load forecasting helps in unit commitment as well as in economic scheduling of the generators. The price forecasting helps an electric utility to make important decisions like generation of electric power, bidding for generation, price switching and infrastructure development. Price forecasting is very much useful for energy suppliers, ISOs and other participants in electric generation, transmission and distribution. This paper presents a hybrid approach for the STLF and STPF. The time series data pertaining to load / price is decomposed into various decomposition levels by the use of Wavelet Transform (WT) and each level obtained by this process is predicted using Artificial Neural Network (ANN). The performance of the proposed hybrid model is validated using New Delhi load data and Ontario electricity price data.
Keywords :
electricity supply industry; load forecasting; power system economics; pricing; wavelet transforms; artificial neural network; daily power market; deregulated power industry; economic scheduling; electric utility; hybrid approach; price forecasting; short term electricity price; short term load forecasting; unit commitment; wavelet transform; Artificial neural networks; Forecasting; Load forecasting; Load modeling; Predictive models; Wavelet transforms; ANN; Load forecasting; Price forecasting; Wavelet Transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Energy, Automation, and Signal (ICEAS), 2011 International Conference on
Conference_Location :
Bhubaneswar, Odisha
Print_ISBN :
978-1-4673-0137-4
Type :
conf
DOI :
10.1109/ICEAS.2011.6147110
Filename :
6147110
Link To Document :
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