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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
Shahrizal Jelani
UCSI University
Computer Science & IT Electrical & Electronics Engineering Engineering

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Journal : Bulletin of Electrical Engineering and Informatics

 1 
Tap changer optimisation using embedded differential evolutionary programming technique for loss control in power system Ahmad Faris; Ismail Musirin; Shahrizal Jelani; Saiful Amri Ismail; Mohd Helmi Mansor; A. V. Senthil Kumar
Bulletin of Electrical Engineering and Informatics Vol 9, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v9i6.2505

Abstract

Over-compensation and under-compensation phenomena are two undesirable results in power system compensation. This will be not a good option in power system planning and operation. The non-optimal values of the compensating parameters subjected to a power system have contributed to these phenomena. Thus, a reliable optimization technique is mandatory to alleviate this issue. This paper presents a stochastic optimization technique used to fix the power loss control in a high demand power system due to the load increase, which causes the voltage decay problems leading to current increase and system loss increment. A new optimization technique termed as embedded differential evolutionary programming (EDEP) is proposed, which integrates the traditional differential evolution (DE) and evolutionary programming (EP). Consequently, EDEP was for solving optimizations problem in power system through the tap changer optimizations scheme. Results obtained from this study are significantly superior compared to the traditional EP with implementation on the IEEE 30-bus reliability test system (RTS) for the loss minimization scheme.
Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system Nur Ainna Shakinah Abas; Ismail Musirin; Shahrizal Jelani; Mohd Helmi Mansor; Naeem M. S. Honnoon; Muhammad Murtadha Othman
Bulletin of Electrical Engineering and Informatics Vol 8, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (598.604 KB) | DOI: 10.11591/eei.v8i3.1631

Abstract

This paper presents the optimal multiple distributed generations (MDGs) installation for improving the voltage profile and minimizing power losses of distribution system using the integrated monte-carlo evolutionary programming (EP). EP was used as the optimization technique while monte carlo simulation is used to find the random number of locations of MDGs. This involved the testing of the proposed technique on IEEE 69-bus distribution test system. It is found that the proposed approach successfully solved the MDGs installation problem by reducing the power losses and improving the minimum voltage of the distribution system.
Co-Authors A. V. Senthil Kumar A.V.Senthil Kumar Ahmad Faris Farah Adilah Jamaludin Fareed Danial Ahmad Kahar Ismail Musirin Ismail Musirin Mohd Helmi Mansor Muhamad Faliq Mohamad Nazer 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