NDLI: One hour ahead price forecast of Ontario electricity market by using ANN

Content Provider	IEEE Xplore Digital Library
Author	Sahay, K.B.
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. Eng., Madan Mohan Malaviya Univ. of Technol., Gorakhpur, India (Sahay, K.B.)
Abstract	In restructured electricity markets, forecasting electricity parameters are most essential tasks & basis for any decision making. Forecasting price in competitive electricity markets is difficult for consumers and producers in order to plan their operations and to manage their price risk, and it also plays a key role in the economic optimization of the deregulated power industry. Accurate, short-term price forecasting is an essential instrument which provides crucial information for power producers and consumers to develop accurate bidding strategies in order to maximize their profit. In this paper artificial intelligence (AI) has been applied in short-term price forecasting that is, the one hour ahead price forecast of the electricity market. A new artificial neural network (ANN) has been used to compute the forecasted price in Ontario electricity market using MATLAB R13b. The data used in the forecasting are hourly historical data of the electricity load and price of Ontario electricity market. The simulation results have shown highly accurate one hour ahead forecasts with very small error in price forecasting.
Starting Page	1
Ending Page	6
File Size	493803
Page Count	6
File Format	PDF
ISBN	9781467374910
e-ISBN	9781467374927
DOI	10.1109/EnergyEconomics.2015.7235102
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-03-27
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mean absolute error (MAE) Mean absolute percentage error (MAPE) Neurons Artificial neural networks One hour ahead electricity price forecast Forecasting Biological neural networks Power system Short-term price forecasting Neural network (NN) Electricity supply industry Data models Locational marginal price (LMP) Load modeling
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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