Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Muhamad Faliq Mohamad Nazer
UCSI University
Computer Science & IT Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Supervised evolutionary programming based technique for multi-DG installation in distribution system Muhammad Firdaus Shaari; Ismail Musirin; Muhamad Faliq Mohamad Nazer; Shahrizal Jelani; Farah Adilah Jamaludin; Mohd Helmi Mansor; A.V.Senthil Kumar
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 1: March 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (650.398 KB) | DOI: 10.11591/ijai.v9.i1.pp11-17

Abstract

Installing DG in network system, has supported the distribution system to provide the increasing number of consumer demand and load, in order to achieve that this paper presents an efficient and fast converging optimization technique based on a modification of traditional evolutionary programming method for obtain the finest optimal location and power loss in distribution systems. The proposed algorithm that is supervised evolutionary programming is implemented in MATLAB and apply on the 69-bus feeder system in order to minimize the system power loss and obtaining the best optimal location of the distributed generators. 
Index-based transmission for distributed generation in voltage stability and loss control incorporating optimization technique Fareed Danial Ahmad Kahar; Ismail Musirin; Muhamad Faliq Mohamad Nazer; Shahrizal Jelani; Mohd Helmi Mansor
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 2: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (699.683 KB) | DOI: 10.11591/ijai.v9.i2.pp244-251

Abstract

The integration of Distributed Generation (DG) in a distribution network may significantly affect distribution performance. With the penetration of DG, voltage security is no longer an issue in the transmission network. This paper presents a study of Distributed Generation on the IEEE 26-Bus Reliability Test System (RTS) with the use of Fast Voltage Stability Index (FVSI) for determining its location and incorporated with Grasshopper Optimization Algorithm (GOA) to optimize the sizing of the DG. The study emphasizes the power loss of the system in which a comparison between Evolutionary Programming (EP) and Grasshopper Optimization Algorithm is done to determine which optimization technique gives an optimal result for the DG solution. The results show that the proposed algorithm is able to provide a slightly better result compared to EP.
Co-Authors A.V.Senthil Kumar Farah Adilah Jamaludin Fareed Danial Ahmad Kahar Ismail Musirin Ismail Musirin Mohd Helmi Mansor Muhammad Firdaus Shaari Shahrizal Jelani