This paper presents the Gravitational Search Algorithm (GSA), a multi-objective enhancement method that may be functional to distribution systems to optimize capacity, capacitor bank and DG unit position, and network reconfiguration. Section load ability, voltage deviation, reactive and active power losses, voltage stability index, and balancing current index are the six performance indices that make up the objective function. Both the composition and significance of each indicator are taken into account by the optimization problem’s objective function. The suggested GSA method was evaluated against three new recognized algorithms: The GA, PSO, and techniques, using tests conducted on IEEE 33 and 69 bus systems. The simulation’s findings demonstrate how the GSA algorithm can maximize the capacity and position of capacitor banks and DG sources in various operating scenarios, improving system performance and reducing active losses in the network.

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Gravitational Search Algorithm Based Optimal Position of DG and Capacitor with Restructuring

  • D. Mahesh Kumar,
  • S. Suresh Reddy,
  • P. Sujatha

摘要

This paper presents the Gravitational Search Algorithm (GSA), a multi-objective enhancement method that may be functional to distribution systems to optimize capacity, capacitor bank and DG unit position, and network reconfiguration. Section load ability, voltage deviation, reactive and active power losses, voltage stability index, and balancing current index are the six performance indices that make up the objective function. Both the composition and significance of each indicator are taken into account by the optimization problem’s objective function. The suggested GSA method was evaluated against three new recognized algorithms: The GA, PSO, and techniques, using tests conducted on IEEE 33 and 69 bus systems. The simulation’s findings demonstrate how the GSA algorithm can maximize the capacity and position of capacitor banks and DG sources in various operating scenarios, improving system performance and reducing active losses in the network.