NDLI: Day-Ahead Deregulated Electricity Market Price Forecasting Using Recurrent Neural Network

Content Provider	IEEE Xplore Digital Library
Author	Anbazhagan, S. Kumarappan, N.
Copyright Year	2007
Abstract	This paper proposes a recurrent neural network model for the day ahead deregulated electricity market price forecasting that could be realized using the Elman network. In a deregulated market, electricity price is influenced by many factors and exhibits a very complicated and irregular fluctuation. Both power producers and consumers need a single compact and robust price forecasting tool for maximizing their profits and utilities. In order to validate the chaotic characteristic of electricity price, an Elman network is modeled. The proposed Elman network is a single compact and robust architecture (without hybridizing the various hard and soft computing models). It has been observed that a nearly state of the art Elman network forecasting accuracy can be achieved with less computation time. The proposed Elman network approach is compared with autoregressive integrated moving average (ARIMA), mixed model, neural network, wavelet ARIMA, weighted nearest neighbors, fuzzy neural network, hybrid intelligent system, adaptive wavelet neural network, neural networks with wavelet transform, wavelet transform and a hybrid of neural networks and fuzzy logic, wavelet-ARIMA radial basis function neural networks, cascaded neuro-evolutionary algorithm, and wavelet transform, particle swarm optimization, and adaptive-network-based fuzzy inference system approaches to forecast the electricity market of mainland Spain. Finally, the accuracy of the price forecasting is also applied to the electricity market of New York in 2010, which shows the effectiveness of the proposed approach.
Sponsorship	IEEE Systems Council
Starting Page	866
Ending Page	872
Page Count	7
File Size	374414
File Format	PDF
ISSN	19328184
Volume Number	7
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Forecasting Electricity Electricity supply industry Computational modeling Predictive models Neurons Biological neural networks recurrent neural network Deregulated electricity market electricity price forecasting Elman network
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Control and Systems Engineering Information Systems Electrical and Electronic Engineering Computer Science Applications

Sl.	Authority	Responsibilities	Communication Details
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
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
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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