This paper offers an approach for distribution system recon figuration (DSR) in order to reduce active power loss, switching operations, and improve the system small signal and voltage stability margin with the consideration of branch current carrying capacity, bus voltage, and distribution system radiality constraints in the presence of DGs. Nondominated sorting genetic algorithm-II (NSGA-II) is used to find the pareto-optimal solutions of this limited multi-objective optimization problem. The optimum solution among the resulting pareto-optimal solutions is then determined using the max-min technique. To show the viability and efficacy of the suggested approach, tests have been conducted on IEEE 33-bus, 69-bus, and 119-bus radial distribution systems. The findings acquired by using the multi-objective genetic algorithm (GA) method have also been compared with the acquired findings.

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Distribution System Reconfiguration with Stability Consideration in the Presence of DGs

  • Jyoti Shukla,
  • Basanta K. Panigrahi,
  • Deepti Arela,
  • Subhendu Pati

摘要

This paper offers an approach for distribution system recon figuration (DSR) in order to reduce active power loss, switching operations, and improve the system small signal and voltage stability margin with the consideration of branch current carrying capacity, bus voltage, and distribution system radiality constraints in the presence of DGs. Nondominated sorting genetic algorithm-II (NSGA-II) is used to find the pareto-optimal solutions of this limited multi-objective optimization problem. The optimum solution among the resulting pareto-optimal solutions is then determined using the max-min technique. To show the viability and efficacy of the suggested approach, tests have been conducted on IEEE 33-bus, 69-bus, and 119-bus radial distribution systems. The findings acquired by using the multi-objective genetic algorithm (GA) method have also been compared with the acquired findings.