NDLI: Neural network models to predict short-term electricity prices and loads

Content Provider	IEEE Xplore Digital Library
Author	Mandal, P. Senjyu, T. Funabashi, T.
Copyright Year	2005
Description	Author affiliation: Dept. of Electr. & Electron. Eng., Ryukyus Univ., Okinawa (Mandal, P.; Senjyu, T.)
Abstract	Forecasting hourly electricity prices and loads in daily power markets is the most essential task and basis for any decision making. An approach to predict the market behaviors is to use the historical prices, loads and other required information to forecast the future prices and loads. This paper presents an approach for short-term electricity price and load forecasting using neural network model, which uses publicly available data from NEMMCO Web site to forecast electricity price and load for the Victorian electricity market. An approach of selection of similar days is proposed according to which the load and price curves are forecasted by using the information of the days being similar to that of the forecast day. A Euclidean norm with weighted factors is used for the selection of similar days. Two different ANN models, one for load forecasting and another for price forecasting have been proposed. The forecasted price and load from the neural networks are the corrected output of selected similar price and load days, respectively. MAPE results show that short-term electricity prices and loads in the deregulated Victorian market can be forecasted with reasonable accuracy
Starting Page	164
Ending Page	169
File Size	657033
Page Count	6
File Format	PDF
ISBN	0780394844
DOI	10.1109/ICIT.2005.1600629
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-12-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Predictive models Load forecasting Economic forecasting Power markets Decision making Electricity supply industry Artificial neural networks Load modeling Electricity supply industry deregulation similar days Short-term price and load forecasting neural networks power market
Content Type	Text
Resource Type	Article

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