Optimal Distributed Generation Planning in Radial Distribution Systems Using Body Immune Algorithm

This paper presents a new methodology based on the Body Immune Algorithm for optimal placement and estimation of distributed generator (DG) capacity in the radial distribution systems in order to reduce the real power losses and improve the voltage profile and un-supplied energy. The proposed method considers the options of the DGs installation and takes more number of significant parameters into account compare to the previous studies that consider only a few parameters in their optimization algorithms. Some of the socalled cost parameters considered in the proposed approach are: loss reduction, voltage profile improvement, environmental effects, fuel price and costs of load prediction for each bus. Using an optimal Body Immune Algorithm in the proposed optimization method, a destination function that includes all of the abovementioned cost parameters has been optimized. Furthermore, this method is capable of changing the weights of each cost parameter in the destination function of the Body Immune Algorithm as well as the matrix of coefficients in the DIGSILENT environment. The proposed method has been applied and simulated on a sample IEEE 9-bus network. The obtained results show that any change in the weight of each parameter in the destination function of the Body Immune Algorithm and in the matrix of coefficients leads to a meaningful change in the prediction of the location and capacity of the prospective DG.