The development of congestion management of a deregulated power system using fuzzy logic

Samsudin, Adam and Sari, Clara and Azmi, Ezzatul Farhain and Jaffar, Kamilah and Md Sarif, Norhafizah (2022) The development of congestion management of a deregulated power system using fuzzy logic. International Journal Of Electrical Engineering And Applied Sciences (IJEEAS), 5 (2). pp. 1-09. ISSN 2600-7495

Text 6119-ARTICLE TEXT-17666-1-10-20221031_IJEEAS.PDF Download (1MB)

Abstract

Deregulated power system is a method of altering the existing regulatory structure of the power market in order to: reduce costs, draw new investments in power market and increase efficiency. Reforming the power market into a deregulated system reduce the transmission capacity since there will be more investors occupying the power system causing congestion in lines. Thus, the objectives of this paper is to present congestion management method in a deregulated market by analysing the congestion levels in transmission lines using Fuzzy Logic Approach. The Fuzzy method can be used to classify the levels of congestion in the transmission lines, resulting in easier monitoring of which lines are moderately or heavily loaded for pricing purposes based on usage. Thus, the congestion levels are to be defined depending on the price of power charged and amount of load used by end users. The congestion levels classifications were tested on IEEE Reliability Test System 1996 24 Bus System using its Weekly and Daily Peak Load Data.

Item Type:	Article
Uncontrolled Keywords:	congestion management, deregulated, power system, fuzzy logic
Divisions:	Faculty of Mechanical and Manufacturing Engineering Technology
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	06 Mar 2023 15:24
Last Modified:	06 Mar 2023 15:24
URI:	http://eprints.utem.edu.my/id/eprint/26483
Statistic Details:	View Download Statistic

Actions (login required)

View Item