Optimal Distributed Generation Placement in Radial Distribution Networks Using Enhanced Search Group Algorithm

The aim of this research is to define the placement of distributed generations (DGs) in radial distribution networks (RDNs) using a meta-heuristic method called the Enhanced Search Group Algorithm (ESGA). This algorithm is an upgraded version of the conventional SGA that incorporates the Chaotic Local Search (CLS) approach to improve global exploration ability. The purposes of the optimal DG placement (ODGP) problem are to decrease active power losses, increase voltage stability, and boost the voltage profile of RDNs. The study applied the ESGA to optimize the placement and size of DGs, considering two cases of power factors (unity and optimal) in 33, 69, and 118-bus RDNs. Based on the optimal results, employing optimal power factors in operating DGs pointedly enhances the performance of RDNs by decreasing power loss, reducing voltage deviation, and increasing voltage stability. The ESGA method outperforms other approaches regarding solution quality, indicating its effectiveness in resolving ODGP problems, particularly for large-scale and complex networks.

Automated summary

This research aims to define the placement of distributed generations (DGs) in radial distribution networks (RDNs) using Enhanced Search Group Algorithm (ESGA). The study found that operating DGs with optimal power factors significantly improves the performance of RDNs by reducing losses, lowering voltage deviation, and increasing voltage stability. The ESGA method is more effective in solving the optimal DG placement problem compared to other approaches.