DG Source Allocation by Fuzzy and Clonal Selection Algorithm for Minimum Loss in Distribution System

摘要

Distributed Generation (DG) is a promising solution to many power system problems such as voltage regulation, power loss, etc. This article presents a new methodology using Fuzzy and Artificial Immune System (AIS) for the placement of Distributed Generators (DGs) in a radial distribution system to reduce the real power losses and to improve the voltage profile. A two-stage methodology is used for the optimal DG placement. In the first stage, the Fuzzy Set approach is used to find the optimal DG locations and in the second stage, Clonal Selection algorithm of AIS is used to size the DGs corresponding to maximum loss reduction. This algorithm is a new, population based, optimization method inspired by the cloning principle of the human body immune system. The advantage of this algorithm is the population size is dynamic and it is determined by the fitness values of the population. The proposed method is tested on standard IEEE-33 based bus test system. Net, the results are compared with different approaches available in the literature. The proposed method outperforms the other methods in terms of the quality of solution and computational efficiency.