TY  - EJOU
AU  - Kumar, S. Arun 
AU  - Padma, S. 
AU  - Madhubalan, S. 

TI  - Distribution Network Reconfiguration Using Hybrid Optimization Technique
T2  - Intelligent Automation \& Soft Computing

PY  - 2022
VL  - 33
IS  - 2
SN  - 2326-005X

AB  - Energy management carried in a power system by configuration process is a difficult activity. So, reconfiguration has been introduced to solve this problem. Numerous optimization topologies have been utilized to solve this problem so far. However, they exhibit some drawbacks such as convergence, etc. Hence to overcome this issue, this work formulated a new hybrid optimization topology Genetic Algorithm Enabled Particle Swarm Optimization (PSOGA) to solve the energy configuration problem with low power loss in the Distribution System (DS). The proposed topology’s effectiveness was evaluated on the IEEE 33 bus Distribution System, and the results were compared to methods reported in the literature. As a result, the suggested technique appears to be more successful than other approaches, and the power loss in buses is minimised and hence exhibits an enhanced voltage profile. Hence, it is concluded that the proposed PSOGA can be a promising topology for reconfiguration as well as energy management in DS.
KW  - Energy management; distribution system (DS); network re-configuration (NR); distributed generation (DG); genetic algorithm enabled particle swarm optimization (PSOGA); power loss

DO  - 10.32604/iasc.2022.023702