A Novel Hybrid Optimization Technique for Network Reconfiguration with Dispersed Generators Placement in Distribution System

The integration of Distributed Generation (DG) into electrical networks offers a valuable approach to improving power system performance. This paper introduces a hybrid algorithm that merges the strengths of Binary Particle Swarm Optimization (BPSO) and the Cuckoo Search Algorithm (CSA) to optimize the placement of DGs in power networks. The key objectives are to minimize power losses and enhance voltage profiles, both of which are essential for maintaining a reliable and efficient power system. The proposed methodology employs a multi-objective optimization framework to address these goals concurrently, leading to improved system reliability and economic benefits. The hybrid algorithm's effectiveness is demonstrated through case studies on the IEEE 33-bus test system, showing superior performance compared to conventional methods. Results reveal considerable reductions in power losses and notable improvements in voltage profiles, highlighting the advantages of optimal DG placement. Additionally, the study underscores the cost savings from reduced energy losses, translating into long-term economic benefits for both utility operators and consumers. The findings emphasize the role of advanced optimization techniques in modernizing power distribution systems and supporting sustainable energy solutions.