Developed Algorithm Based on Lightning Search optimizer and Analytical Technique for Allocation of Distribution Generators

This paper proposes a combined analytical and metaheuristic optimization algorithm for optimal allocation of multiple types of Distributed Generators (DGs) in radial distribution networks to minimize the total power losses. The analytical technique based on the exact loss formula is used to calculate the optimal size of the DG unit at a certain bus. However, the analytical technique may not be suitable to allocate multiple DGs types due to the mass of calculations, hence, Lightning Search Algorithm (LSA) is combined with the analytical technique to find the optimal locations. Like any random search-based optimization algorithm, LSA faces some issues such as low convergence rate and trapping in local solutions. So, to avoid these kinds of problems, a proposed Chaotic LSA (CLSA) based on Gauss/mouse map is established. The gauss/mouse map is used to change random LSA forking occurrence instead of using the random variable. The proposed Combined Analytical CLSA (CA-CLSA) is validated using the stranded radial distribution feeders such as 15 and 30-networks. A comprehensive comparison between the proposed technique and other competitive optimization techniques is carried out to prove its effectiveness. The result shows that the proposed combined analytical CA-CLSA is efficient to allocate the multiple DGs types with minimum power loss and high convergence rate.