Allocation and Estimation of DG Capacity in Distribution Networks by Particle Swarm Optimization

This paper presents optimal placement and estimation of distributed generation (DG) capacity using Particle Swarm Optimization (PSO) approach in the radial distribution systems to reduce the real power losses and to gain voltage profile improvement. Furthermore, the proposed method focuses on the installation of the DGs and takes more number of significant parameters into account compare to the previous studies which consider only a few parameters for their optimization algorithms. Some of the so-called cost parameters considered in the proposed approach is loss reduction, voltage profile improvement, fuel price and costs of load prediction for each bus. Using an optimal PSO Algorithm, the proposed optimization method, a destination function that includes all of the cost parameters, has been optimized. This method is also capable of changing the weights of each cost parameter in the destination function of the PSO Algorithm and the matrix of coefficients in the DIGSILENT environment. The cost parameters are variables dependent on the status and position of each bus in the network, putting forth an optimal DG placement. The proposed method has been applied and simulated on a sample IEEE 33bus network. The obtained results show that any change in the weight of each parameter in the destination function of the PSO Algorithm and in the matrix of coefficients leads to a meaningful change in the location and capacity of the prospective DG in the distribution network.