METAHEURISTIC BASED TECHNIQUES FOR OPTIMAL SIZING AND SITING OF DISTRIBUTED GENERATIONS IN RADIAL DISTRIBUTION NETWORK

An artificial intelligent (AI) based approach for optimal insertion and sizing of distributed generations (DGs) in distribution network is addressed in this research study. The objective function is constituted by considering different functions and this function is optimized by using AI based techniques. Further, basic objective of this study is to minimize the designed function under given constraints. The objective function is consisting system active power loss with DG and active power loss without DG, the ratio of bus voltage after DG to bus voltage before DG, and reciprocal of index of voltage stability. In this research article GA, PSO and GA-PSO hybrid based techniques are investigated to optimize the designed objective function. The proposed algorithms are applied on IEEE 69-bus test distribution network. From the simulation results it realized that all considered techniques produced almost similar results but computational time of GA is more further it is observed that GA-PSO based hybridized technique is better in terms of optimization of different parameters. It is concluded on basis of results that GA-PSO based technique is slightly better as compare GA, PSO in reference loss minimization, and system voltage improvement.