Optimal integration of distributed generators in medium-voltage radial distribution systems using enhanced particle swarm optimization algorithm

Abstract

Due to the enormous demand for electrical energy and the deregulation of the power system, distributed generator integration in power networks has grown more common in recent years. To optimize distribution feeder performance, these distributed generators must be positioned properly. In order to distribute DGs in a radial distribution network as efficiently as possible, this study attempts to develop an adaptive optimization metaheuristic method. There are two primary stages to the research process used to achieve the goal. Using the MATLAB Simulink platform, the IEEE 33 bus benchmark system is first created and tested in several scenarios, including placing a DG at various busbars, having numerous DGs, and having a DG with varying capacity. The best allocation of DGs is then solved in the second phase using an improved particle swarm technique that is implemented in the MATLAB platform. Five DGs are used to optimize the voltage constraint within the voltage profile's added upper and lower bounds. The optimization findings show that the IEEE 33 bus system operates best when five DGs with capacities of 446 kW, 1802 kW, 404 kW, 502.5 kW, and 401 kW are installed at busbars 7, 12, 19, 25, and 26 accordingly with a loss reduction percentage of 54.23%. Power system engineers and academics who want to optimally allocate the distributed energy resources in order to enhance distribution network performance will benefit from the findings.