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Transmission usage allocation in bilateral energy transaction using artificial neural network

Mustafa, Mohd. Wazir and Shareef, Hussain and Abd. Khalid, Saifulnizam and Khairuddin, Azhar (2008) Transmission usage allocation in bilateral energy transaction using artificial neural network. In: Power Flow Allocation Approaches In Deregulated Power System. Penerbit UTM, Johor, pp. 71-90. ISBN 978-983-52-0679-5

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Official URL: http://www.penerbit.utm.my/bookchapterdoc/FKE/book...

Abstract

Recent trends in the bulk power consumer have been towards into bilateral transactions service with electric power utilities to avoid price fluctuations of energy market in a deregulated environment. Electric power utilities need to know the actual cost of providing unbundled services in order to make correct economic decisions that they should promote or curtail while considering their service obligations. As part of these trends, the emphasis on the knowledge of providing unbundled transmission service has been important and increase steadily. The concept of bilateral transactions allows the consumers and utilities to work according to their policy and does not make them dependent on everyday bid like in a pool model. Bilateral transactions enable consumers to make their best price deals for generation supply with whoever in the competitive market is most effective to meet their load demand. Allowing supplier to transact directly with consumers creates competition in terms of pricing, contract duration, payment terms, type of generation and type of electric service on both sides of the transaction. Generators compete among themselves to supply this demand. This gives consumers a full range of choices among generator. Thus, bilateral transactions will provide a wide range of choices to meet various customer needs.

Item Type:Book Section
Uncontrolled Keywords:bilateral transactions, neural network, transmission
Subjects:T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:27754
Deposited By: Fazli Masari
Deposited On:08 Aug 2012 05:43
Last Modified:08 Aug 2012 05:52

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