Distributed Generation Allocation in Distribution System using Particle Swarm Optimization based Ant-Lion Optimization
This research proposed an effective method to get better Distributed Generation (DG) place and capacity in Radial Distribution Scheme (RDS). Here efficient technique is obtained by hybridization Ant-Lion Optimization (ALO) and the performance is improved with the help of PSO function. This ALO technique imitates the catching behavior of ant lions in general. Novelty of the proposed technique is to find the maximum power loss position of the RDS and placing the optimal DG from the given PV (Photo Voltaic), WT (Wind Turbine) and Diesel Generator. Primarily, the load-flow investigation of RDS is performed for measures the power losses of the RDS. Because of the load variation, the voltage profile, actual power loss and voltage stability indexes (VSI) are investigated. Following that, the weak buses are acknowledged on the basis of the VSI and power loss factors and fixing the DG. After placement the DG, the VSI and power loss is diminished and maximization of voltage profile. This projected scheme is executed with MATLAB software and validated on the IEEE 33 radial system. Effectiveness of the projected methodology is determined and evaluated with standalone techniques like conventional ALO, Gravitational Search Algorithm (GSA) and Bat algorithm.