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All Journal Indonesian Journal of Electrical Engineering and Computer Science
M. M. Othman
Universiti Teknologi MARA

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

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Multiple DG Planning Considering Distribution Loss and Penetration Level using EMEFA-ANN Method S. R. A. Rahim; I. Musirin; M. M. Othman; M. H. Hussain
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp1-8

Abstract

This paper presents the implementation of multiple distributed generation planning in distribution system using computational intelligence technique. A pre-developed computational intelligence optimization technique named as Embedded Meta EP-Firefly Algorithm (EMEFA) was utilized to determine distribution loss and penetration level for the purpose of distributed generation (DG) installation. In this study, the Artificial Neural Network (ANN) was used in order to solve the complexity of the multiple DG concept. EMEFA-ANN was developed to optimize the weight of the ANN to minimize the mean squared error. The proposed method was validated on IEEE 69 Bus distribution system with several load variations scenario. The case study was conducted based on the multiple unit of DG in distribution system by considering the DGs are modeled as type I which is capable of injecting real power. Results obtained from the study could be utilized by the utility and energy commission for loss reduction scheme in distribution system.
Application of Immune Log-Normal Evolutionary Programming in Distributed Generation Installation M. H. Mansor; I. Musirin; M. M. Othman; S. A. Shaaya; S. A. Syed Mustaffa
Indonesian Journal of Electrical Engineering and Computer Science Vol 6, No 3: June 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v6.i3.pp730-736

Abstract

Nowadays, the location and sizing of distributed generation (DG) units in power system network are crucial to be at optimal as it will affect the power system operation in terms of stability and security. In this paper, a new technique termed as Immune Log-Normal Evolutionary Programming (ILNEP) is applied to find the optimal location and size of distributed generation units in power system network. Voltage stability is considered in solving this problem. The proposed technique has been tested on the IEEE 26 bus Reliability Test System to find the optimal location and size of distributed generation in transmission network. In order to study the performance of ILNEP technique in solving DG Installation problem, the results produced by ILNEP were compared with other meta-heuristic techniques like evolutionary programming (EP) and artificial immune system (AIS). It is found that the proposed technique gives better solution in term of lower total system loss compared to the other two techniques.
Co-Authors I. Musirin M. H. Hussain M. H. Mansor S. A. Shaaya S. A. Syed Mustaffa S. R. A. Rahim