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

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