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

Research output: Contribution to journalArticle

7 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)721-729
Number of pages9
JournalIndonesian Journal of Electrical Engineering and Computer Science
Issue number3
Publication statusPublished - 01 Jun 2017

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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