Multi population evolutionary programming approach for distributed generation installation

Baharom, Mohamad Faizal and Jali, Mohd Hafiz and Wan Daud, Wan Mohd Bukhari and Bohari, Zul Hasrizal and Mohd Nasir, Mohamad Na'im (2014) Multi population evolutionary programming approach for distributed generation installation. TELKOMNIKA: Telecommunication, Computing, Electronics and Control, 12 (3). pp. 541-548. ISSN 1693-6930

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Abstract

This paper describes the impact of development distribution in order to identify optimum location and size for distribution generation (DG) in power system network. High demand on the load will cause unstable control power distributed through power loss via power transmition. Therefore smallscale electricity generation is required to ensure large power generated can be used for particular location to minimize power losses. In addition, the implementation of distribution generation will help to reduce the capital cost compared to the existing power plant due to space, speed and power requirement. Thus proper DG location will significantly improve the impact of the power flow analysis by considering the source of energy which is easily obtained. This study will be conducted by using Matlab and the proposed algorithm (MPEP) will be applied on IEEE 30 buses radial distribution system network. As a result, the DG can be located at optimal location and size depending on the losses consume in various type of DG technology systems used in the network. On the other hand, the condition and location DG itself will generate optimal power contribution depending on design strategies that have been implemented.

Item Type: Article
Uncontrolled Keywords: multi population evolutionary programming, migration, optimal location and sizing, IEEE distribution system
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Electrical Engineering > Department of Industrial Power
Depositing User: MOHAMAD NA'IM MOHD NASIR
Date Deposited: 21 Jan 2015 03:50
Last Modified: 24 Jul 2023 16:40
URI: http://eprints.utem.edu.my/id/eprint/13969
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