Optimal allocation and sizing of multiple distributed generators in distribution networks using a novel hybrid particle swarm optimization algorithm

Abstract

Optimal Integration of Distributed Generation (DG) in distribution grid is one of the important and effective options. Optimal allocation with a suitable sizing of DG units play efficient role in reducing operating cost and power losses in additional to improving voltage stability which are considered in optimization objective function. In this paper, a new effective and powerful optimization algorithm is produced. A novel hybrid particle swarm (HPSO) with Quasi-Newton (QN) algorithm is proposed to solve the problem of DG location and sizing distribution systems satisfying the operation constraints. In this paper, two stages are introduced. First, the loss sensitivity analysis is employed to select the most appropriate candidate DG placement. Then, a novel hybrid particle swarm optimization (HPSO) algorithm is implemented to find optimal sizing of DGs and their settings from the selected buses. The proposed algorithm has been tested on 33-bus, and 69-bus IEEE standard radial distribution systems under multi distributed generator types. In order to validate the proposed approach, the obtained 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 proved the capability with good performance of the proposed approach to find the optimal solutions. Numerical results have been obtained by MATLAB package.