NDLI: A neural network based short term load forecasting model

Content Provider	IEEE Xplore Digital Library
Author	Sharaf, A.M. Lie, T.T. Gooi, H.B.
Copyright Year	1994
Description	Author affiliation: Dept. of Electr. Eng., New Brunswick Univ., Fredericton, NB, Canada (Sharaf, A.M.)
Abstract	A novel feedforward two layer ANN neural network based function approximator model is utilized to forecast electric system hourly load. The forecast model is based on a quantitative weight assignment priority factors for the day type and daytime classes, in addition to the daily average temperature. The forecast vector utilizes scaled historical load data for eight day type classes, four day time subclasses as well as load pattern averaged one-hour, six-hour, 24-hour, and 168-hour filtered historical load. To improve the neural network training load, additional variables such as cross correlation and FFT spectra were utilized. To allow for online implementation, the forecast vector was also augmented with the estimated load first and second differential variations. The new ANN-based short term load forecast (STLF) model was tested using two month data sample of the Singapore Public Utilities Board (PUB) historical data.<>
Starting Page	325
Ending Page	328
File Size	268873
Page Count	4
File Format	PDF
ISBN	0780324161
DOI	10.1109/CCECE.1993.332322
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1993-09-14
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Load forecasting Load modeling Predictive models Artificial neural networks Technology forecasting Weather forecasting SCADA systems Data preprocessing Niobium
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
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
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8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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