Optimal Placement of Distributed Generation Using Particle Swarm Optimization

This paper proposes a particle swarm optimization (PSO) algorithm for optimal placement of distributed generation (DG) in a primary distribution system to minimize the total real power loss. The PSO provides a population-based search procedure in which individuals called particles change their positions with time. During flight, each particle adjusts its position according to its own experience, and the experience of neighboring particles, making use of the best position encountered by itself and its neighbors. Initially, the algorithm randomly generates the particle positions representing the size and location of DG. Each particle will move from its current position using the velocity and the distance from current best local and global solution reached. The velocity consists of inertia of the particle, memory, and cooperation between particles. The proposed PSO algorithm is used to determine optimal sizes and locations of multi-DGs. Three types of DG are considered and the distribution load flow is used to calculate the exact loss. Test results indicate that PSO method can obtain better results than the simple heuristic search method on the 33-bus and 69-bus radial distribution systems. The PSO can obtain maximum loss reductions for each of three types of optimally placed multi-DGs. Moreover, voltage profile improvement and branch current reduction are obtained