Optimal sitting and sizing of renewable distributed generations in distribution networks using a hybrid PSOGSA optimization algorithm

Abstract

Integration of renewable Distributed Generation (DG) such as Photovoltaic (PV) system and wind turbine (WT) in distribution networks can be considered as brilliant and efficient solution to the growing demands. This paper introduces a new robust and effective hybrid PSOGSA optimization algorithm that proposed to detect the optimal location with convenient size of DG units for minimizing system power losses and operating cost besides improving voltage stability. This paper provides two stages. First, the Loss Sensitivity Factors (LSFs) are employed to select the most candidate buses for DG placement. In the second stage, the PSOGSA is implemented to deduce the optimal sitting and sizing of DG from the elected buses. The proposed scheme has been applied on 33-bus and 69-bus IEEE standard radial distribution systems. To insure the suggested approach validity, the evaluated results have been compared with other algorithms such as Genetic Algorithm (GA), Particle Swarm Algorithm (PSO), Novel combined Genetic Algorithm and Particle Swarm Optimization (GA/PSO), Simulation Annealing Algorithm (SA), and Bacterial Foraging Optimization Algorithm (BFOA). The numerical results have been confirmed the superiority with high performance of the proposed technique to find the optimal solutions of DG units allocation. Numerical results have been attained by MATLAB package.