APPLICATION OF PARTICLE SWARM OPTIMIZATION AND SIMULATED ANNEALING TECHNIQUES FOR OPTIMAL LOCATION AND SIZING OF DISTRIBUTED GENERATORS

Authors

  • S. M. Lawan Department of Electrical Engineering, Kano University of Sci.& Tech, Wudil
  • W. A. W. Z. Abidin Department of Electrical and Electronics Engineering, Universiti Malaysia Sarawak
  • T. Masri Department of Electrical and Electronics Engineering, Universiti Malaysia Sarawak
  • S. J. Kawu Department of Mechanical Engineering, Baze University Abuja

Keywords:

Distributed generation (DG); Particle Swarm Algorithm (PSO), Simulated Annealing, (SA), Voltage Stability Index (FVSI).

Abstract

Distributed Generators (DGs) are generators that produce electrical power from quite a few
modest energy resources. Some could be referred to as on-site generation, dispersed
generation, embedded generation, decentralized generation or distributed energy. These
DGs are located in metropolitan locations if you want to minimize the losses in transmitting
the energy. In order to identify the size of the distributed generators, an optimization
technique is required if the location has been determined. In this study, Fast Voltage Stability
Index (FVSI) is applied to figure out the appropriate location for the DGs while Evolution
Random Number and hybrid Particle Swarm Optimization (PSO) and Simulated Annealing
(SA) were used as the optimization technique to identify the suitable size of the distributed
generators. In order to conduct validation process, the IEEE test system is utilized in this
study. The results show the viability of using the proposed method over genetic algorithm.

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Published

2019-09-25

Issue

Vol. 8 No. 2 (2019)

Section

Articles