Abstract
The present day power distribution network is facing a challenging role to cope up for continuous increasing of load demand. This increasing load demand causes voltage reduction and losses in the distribution network. In current years, the utilization of DG technologies has extremely inflated worldwide as a result of their potential benefits. Optimal sizing and location of DG units near to the load centers provide an effective solution for reducing the system losses and improvement in voltage and reliability. In this paper, the effectiveness of genetic algorithm (GA) and particle swarm optimization (PSO) for optimal placement and sizing of DG in the radial distribution system is discussed. The main advantage of these methods is computational robustness. They provide an optimal solution in terms of improvement of voltage profile, reliability, and also minimization of the losses. They provide the best resolution in terms of improvement of voltage profile, reliability, and also minimization of the losses. The anticipated algorithms are tested on IEEE 33- and 69-bus radial distribution systems using multi-objective function, and results are compared.
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