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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Mohd Helmi Mansor
Universiti Tenaga Nasional
Computer Science & IT Electrical & Electronics Engineering Engineering

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Immunized-Evolutionary Algorithm Based Technique for Loss Control in Transmission System with Multi-Load Increment Sharifah Azwa Shaaya; Ismail Musirin; Shahril Irwan Sulaiman; Mohd Helmi Mansor
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.pp737-748

Abstract

Loss issue is significant in power system since it affects the operation of power system, which ultimately can be translated to monetary effect. Incremental demand that explicitly adding the reactive load causes extra heating losses in the transmission circuit. Without appropriate remedial control, the temperature increase on transmission line cable would end with insulation failure. This phenomenon can be alleviated with a proper compensation scheme that provides optimal solution along with avoidance of under-compensation or over-compensation. Evolutionary Programming (EP) has been recognised as one of the powerful optimisation technique, applied in solving power system problems. Nevertheless, EP is an old technique that sometimes could reach to a settlement that is not fully satisfied. Thus, the need for a new approach to improve the setback is urgent. This paper presents immunized-evolutionary algorithm based technique for loss control in transmission system with multi-load increment. The classical EP was integrated with immune algorithm so as to reduce the computational burden experienced by the classical EP. The algorithm has been tested on a IEEE 12-Bus System and IEEE 14-Bus System. Comparative study was conducted between EP and IEP in terms of optimisation performance. The optimal size and location of PV determined by IEP was able to control the loss in transmission system when the load increases. Results obtained from the studies revealed the merit of the proposed IEP; indicating its feasibility for future implementation in practical system.
Embedded adaptive mutation evolutionary programming for distributed generation management Muhammad Fathi Mohd Zulkefli; Ismail Musirin; Shahrizal Jelani; Mohd Helmi Mansor; Naeem M. S. Honnoon
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i1.pp364-370

Abstract

Distribution generation (DG) is a widely used term to describe additional supply to a power system network. Normally, DG is installed in distribution network because of its small capacity of power. Number of DGs connected to distribution system has been increasing rapidly as the world heading to increase their dependency on renewable energy sources. In order to handle this high penetration of DGs into distribution network, it is crucial to place the DGs at optimal location with optimal size of output. This paper presents the implementation of Embedded Adaptive Mutation Evolutionary Programming technique to find optimal location and sizing of DGs in distribution network with the objective of minimizing real power loss. 69-Bus distribution system is used as the test system for this implementation. From the presented case studies, it is found that the proposed embedded optimization technique successfully determined the optimal location and size of DG units to be installed in the distribution network so that the real power loss is reduced.
Co-Authors A. V. Senthil Kumar A.V.Senthil Kumar Ahmad Faris Chong Kok Hen Farah Adilah Jamaludin Fareed Danial Ahmad Kahar Halimatun Hashim Ismail Musirin Ismail Musirin Ismail Musirin Karmila Kamil Muhamad Faliq Mohamad Nazer Muhammad Amirul Ashraf Ab Rahman Muhammad Fathi Mohd Zulkefli Muhammad Firdaus Shaari Muhammad Haziq Suhaimi Muhammad Murtadha Othman Muzaiyanah Hidayab Naeem M. S. Honnoon Naeem M. S. Honnoon Nur Ainna Shakinah Abas Saiful Amri Ismail Shahril Irwan Sulaiman Shahrizal Jelani Sharifah Azwa Shaaya