K. Dharani Sree^*, P. Karpagavalli

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1181-1195, 2023, DOI:10.32604/iasc.2023.025303

Abstract The distributed generators in the radial distribution network are to improve the Grid performance and its efficiency. These Distributed Generators control the PV bus; it is converted as a remote controlled PVQ bus. This PVQ bus reduces the power loss and reactive power. Initially, the distributed generators were placed in the system using mathematical modelling or the optimization. This approach improves the efficiency but it has no effect in loss minimization. To minimize the loss the reconfigured network with Genetic algorithm based Distributed generator placement proposed as existing work. This approach minimizes the loss effectively; but the genetic algorithm takes… More >

S. Arun Kumar^*, S. Padma, S. Madhubalan

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 777-789, 2022, DOI:10.32604/iasc.2022.023702

Abstract 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… More >