Title :
Day-ahead Electricity Price forecasting using Wavelets and Weighted Nearest Neighborhood
Author :
Bhanu, C. V K ; Sudheer, G. ; RadhaKrishna, C. ; Phanikanth, V.
Author_Institution :
Dept. of Electr. & Electron. Eng., G.V.P. Coll. of Eng., Visakkhapatnam
Abstract :
Price forecasting has been at the center of intense studies since the introduction of competition in electricity industry. Price forecasts are a fundamental input to an energy company´s decision making and strategy development. The present approach is an attempt to forecast day-ahead electricity prices using time series of historical data. A combination of weighted nearest neighborhood and wavelets is used to forecast the next day electricity prices. The methodology is applied to historical data pertaining to California electricity market. The performance of the method is discussed with mean absolute percentage error (MAPE).
Keywords :
power markets; power system economics; pricing; wavelet transforms; California electricity market; day-ahead electricity price forecasting; electricity industry; energy company decision making; energy company strategy development; historical data time series; mean absolute percentage error; wavelets; weighted nearest neighborhood; Consumer electronics; Data engineering; Economic forecasting; Electricity supply industry; Load forecasting; Power engineering and energy; Predictive models; Robustness; Smoothing methods; Wavelet coefficients; Day-ahead electricity prices; forecasting; wavelets; weighted nearest neighborhood;
Conference_Titel :
Power System Technology and IEEE Power India Conference, 2008. POWERCON 2008. Joint International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-1-4244-1763-6
Electronic_ISBN :
978-1-4244-1762-9
DOI :
10.1109/ICPST.2008.4745359
