Prediction Using Learning Coefficients for Efficient Operation of Deregulated Electricity Market

Deregulation and restructuring of electric power industry is occurring in many parts of the world. It is aimed at introducing competition in the supply and retail side of the industry, while maintaining control over the transmission lines. Tracing methodology hence had been introduced to overcome p...

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Main Author:	Perumal, Nallagownden
Format:	Citation Index Journal
Published:	2010
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.utp.edu.my/4715/1/3._American_Journal_SIR-1-3-463-471.pdf http://eprints.utp.edu.my/4715/
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Institution:	Universiti Teknologi Petronas

id	my.utp.eprints.4715
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spelling	my.utp.eprints.47152017-01-19T08:23:49Z Prediction Using Learning Coefficients for Efficient Operation of Deregulated Electricity Market Perumal, Nallagownden TK Electrical engineering. Electronics Nuclear engineering Deregulation and restructuring of electric power industry is occurring in many parts of the world. It is aimed at introducing competition in the supply and retail side of the industry, while maintaining control over the transmission lines. Tracing methodology hence had been introduced to overcome problems related to the Marginal pricing of transmission costs. This paper first analyses of the proportional method which leads to a redefined power tracing method, and then further refines the proposed prediction method by establishing trends of the learning coefficients, using them to examine the relationship between accuracy and number of samples taken. Response of individual generators to change in demand and the corresponding associated losses are also presented. MATLAB with matpower4.0b extension was used to present the study on the IEEE 24bus RTS. 2010-09-20 Citation Index Journal PeerReviewed application/pdf http://eprints.utp.edu.my/4715/1/3._American_Journal_SIR-1-3-463-471.pdf Perumal, Nallagownden (2010) Prediction Using Learning Coefficients for Efficient Operation of Deregulated Electricity Market. [Citation Index Journal] http://eprints.utp.edu.my/4715/
institution	Universiti Teknologi Petronas
building	UTP Resource Centre
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Petronas
content_source	UTP Institutional Repository
url_provider	http://eprints.utp.edu.my/
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Perumal, Nallagownden Prediction Using Learning Coefficients for Efficient Operation of Deregulated Electricity Market
description	Deregulation and restructuring of electric power industry is occurring in many parts of the world. It is aimed at introducing competition in the supply and retail side of the industry, while maintaining control over the transmission lines. Tracing methodology hence had been introduced to overcome problems related to the Marginal pricing of transmission costs. This paper first analyses of the proportional method which leads to a redefined power tracing method, and then further refines the proposed prediction method by establishing trends of the learning coefficients, using them to examine the relationship between accuracy and number of samples taken. Response of individual generators to change in demand and the corresponding associated losses are also presented. MATLAB with matpower4.0b extension was used to present the study on the IEEE 24bus RTS.
format	Citation Index Journal
author	Perumal, Nallagownden
author_facet	Perumal, Nallagownden
author_sort	Perumal, Nallagownden
title	Prediction Using Learning Coefficients for Efficient Operation of Deregulated Electricity Market
title_short	Prediction Using Learning Coefficients for Efficient Operation of Deregulated Electricity Market
title_full	Prediction Using Learning Coefficients for Efficient Operation of Deregulated Electricity Market
title_fullStr	Prediction Using Learning Coefficients for Efficient Operation of Deregulated Electricity Market
title_full_unstemmed	Prediction Using Learning Coefficients for Efficient Operation of Deregulated Electricity Market
title_sort	prediction using learning coefficients for efficient operation of deregulated electricity market
publishDate	2010
url	http://eprints.utp.edu.my/4715/1/3._American_Journal_SIR-1-3-463-471.pdf http://eprints.utp.edu.my/4715/
_version_	1738655364352573440

Prediction Using Learning Coefficients for Efficient Operation of Deregulated Electricity Market

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