NDLI: Day-ahead Electricity Price forecasting using Wavelets and Weighted Nearest Neighborhood

Content Provider	IEEE Xplore Digital Library
Author	Bhanu, C. Sudheer, G. Radhakrishna, C. Phanikanth, V.
Copyright Year	2008
Description	Author affiliation: Dept. of Math., G.V.P. Coll. of Eng. for Women,., Visakahapatnam (Sudheer, G.) \|\| Global Energy consulting Eng. Ltd., Hyderabad (Radhakrishna, C.) \|\| Dept. of Electr. & Electron. Eng., G.V.P. Coll. of Eng., Visakkhapatnam (Bhanu, C.) \|\| Dept. of Electr. & Electron. Eng., G.V.P. Coll. of Eng., Visakhapatnam (Phanikanth, V.)
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).
Starting Page	1
Ending Page	4
File Size	1158776
Page Count	4
File Format	PDF
ISBN	9781424417636
DOI	10.1109/ICPST.2008.4745359
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-12
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robustness Economic forecasting Data engineering Predictive models Power engineering and energy Electricity supply industry Smoothing methods Load forecasting Consumer electronics Wavelet coefficients weighted nearest neighborhood Day-ahead electricity prices forecasting wavelets
Content Type	Text
Resource Type	Article

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