Bacterial Foraging Optimization Technique for Optimal Reorganization of Radial Distribution Network with Inclusion of DG and DSTATCOM
Keywords:
DG, BFOT, DSTATCOM, RDN, AFSOT, ACOTAbstract
Existing transmission infrastructure is unable to handle such a high load demand due to the exponentially expanding demand for electrical power. As a result, either there is a need to make investments to increase the transmission system's capacity or use distributed generation to locally meet consumer demand. Many experts are now focusing on the effect that the growing installation and integration of various small-scale power production technologies into the electrical grid may have on the performance of the grid. The voltage profile is improved and network losses are decreased when the placement and size are ideal. The objective is to choose bus stops where there will be little loss and acceptable potential. Methodology is currently very helpful to the system-planning engineer in dealing with the increase in Distributed Generation (DG) penetration because it can examine the influence on particular system features of DG allocation. In order to improve power quality and optimize DG allocation, a metaheuristic algorithm namely Bacterial Foraging Optimization Technique (BFOT) is developed in this study. A DSTATCOM is added to the system for reactive power compensation in order to increase performance. This aids in loss minimization and voltage quality enhancement. The proposed method is tested on a typical 14-bus & 33-bus radial distribution network (RDN). The simulation is run using Matlab code, and the suggested method's output is compared with Artificial Fish Swarm Optimization Technique (AFSOT) and Ant Colony Optimization Technique (ACOT) and validated against their outputs.
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