Sharifah Azma Syed Mustaffa
Universiti Tenaga Nasional

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

Chaotic Local Search Based Algorithm for Optimal DGPV Allocation Sharifah Azma Syed Mustaffa; Ismail Musirin; Mohd. Murtadha Othman; Mohamad Khairuzzaman Mohamad Zamani; Akhtar Kalam
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 1: July 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i1.pp113-120

Abstract

The advent of advanced technology has led to the increase of electricity demand in most countries in the world. This phenomenon has made the power system network operate close to the stability limit. Therefore, the power utilities are looking forward to the solution to increase the loadability of the existing infrastructure. Integration of renewable energy into the grid such as Distributed Generation Photovoltaic (DGPV) can be one of the possible solutions. In this paper, Chaotic Mutation Immune Evolutionary Programming (CMIEP) algorithm is used as the optimization method while the chaotic mapping was employed in the local search for optimal location and sizing of DGPV. The chaotic local search has the capability of finding the best solution by increasing the possibility of exploring the global minima. The proposed technique was applied to the IEEE 30 Bus RTS with variation of load. The simulation results are compared with Evolutionary Programming (EP)  and it is found that CMIEP performed better in most of the cases.
Chaotic Mutation Immune Evolutionary Programming for Voltage Security with the Presence of DGPV Sharifah Azma Syed Mustaffa; Ismail Musirin; Mohd. Murthada Othman; 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.pp721-729

Abstract

Due to environmental concern and certain constraint on building a new power plant, renewable energy particularly distributed generation photovoltaic (DGPV) has becomes one of the promising sources to cater the increasing energy demand of the power system. Furthermore, with appropriate location and sizing, the integration of DGPV to the grid will enhance the voltage stability and reduce the system losses. Hence, this paper proposed a new algorithm for DGPV optimal location and sizing of a transmission system based on minimization of Fast Voltage Stability Index (FVSI) with considering the system constraints. Chaotic Mutation Immune Evolutionary Programming (CMIEP) is developed by integrating the piecewise linear chaotic map (PWLCM) in the mutation process in order to increase the convergence rate of the algorithm. The simulation was applied on the IEEE 30 bus system with a variation of loads on Bus 30. The simulation results are also compared with Evolutionary Programming (EP) and Chaotic Evolutionary Programming (CEP) and it is found that CMIEP performed better in most of the cases.