COMPARISON OF BACTERIAL FORAGING OPTIMIZATION AND ARTIFICIAL BEE COLONY OPTIMIZATION TECHNIQUE FOR DISTRIBUTED GENERATION SIZING AND PLACEMENT IN AN ELECTRICAL DISTRIBUTION SYSTEM

Integration of Distributed Generation (DG) in an electrical distribution system has increased recently due to voltage improvement, line loss reduction, environmental advantages, and postponement of system upgrading, and increasing reliability. Improper location and capacity of DG may affect the voltage stability on the Distribution System (DS). Optimization techniques are tools used to predict size and locate the DG units in the system, so as to utilize these units optimally within certain limits and constraints. The DG units' sizing and placement is formulated using mixed-integer nonlinear programming, with an objective function of improving the system stability margin; the constraints are the system voltage profile, feeders' capacity, power factor and the DG penetration level. In this paper the optimal sizing and DG placement in distribution systems is presented using Bacterial Foraging Optimization (BFO) and compared with Artificial Bee Colony Optimization (ABCO) algorithm. Two scenarios of DG are considered with some test cases indicate that BFO method can obtain better results than the BCO search method on the 69-bus radial distribution systems