Chaotic local search based algorithm for optimal DGPV allocation

Sharifah Azma Syed Mustaffa, Ismail Musirin, Mohd Murtadha Othman, Mohamad Khairuzzaman Mohamad Zamani, Akhtar Kalam

Research output: Contribution to journalArticle

1 Citation (Scopus)


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.

Original languageEnglish
Pages (from-to)113-120
Number of pages8
JournalIndonesian Journal of Electrical Engineering and Computer Science
Issue number1
Publication statusPublished - Jul 2018

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications
  • Control and Optimization
  • Electrical and Electronic Engineering

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