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This study focuses on the enhancement of reactive power management to minimize energy losses and enhance voltage stability. In order to resolve the Optimal Reactive Power Dispatch (ORPD) issue, it uses a novel population-based Sine–Cosine Algorithm (SCA). The study involves two key computational components: Computational tasks pertaining to the power network are conducted within the DIgSILENT environment, and the heuristic algorithm operations implemented in MATLAB through efficient parallel operation with DIgSILENT. To validate the proposed work effectiveness, testing has been done on IEEE 6- and IEEE 14-bus power systems. The SCA's simulation results are compared with the outcomes of Differential Evolution, Genetic Algorithm, Gray Wolf Optimization and Particle Swarm Optimization. This comparison reveals that the SCA’s performance is superior in addressing the ORPD issue.

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Multi-Objective Approach for Optimal Reactive Power Dispatch Employing Sine Cosine Optimization Algorithm

  • 会议论文

  • 发表日期：

    2025年

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  • Rahul Kumar,
  • Aashish Kumar Bohre,
  • Mohan Lal Kolhe,
  • Sri Niwas Singh

摘要

This study focuses on the enhancement of reactive power management to minimize energy losses and enhance voltage stability. In order to resolve the Optimal Reactive Power Dispatch (ORPD) issue, it uses a novel population-based Sine–Cosine Algorithm (SCA). The study involves two key computational components: Computational tasks pertaining to the power network are conducted within the DIgSILENT environment, and the heuristic algorithm operations implemented in MATLAB through efficient parallel operation with DIgSILENT. To validate the proposed work effectiveness, testing has been done on IEEE 6- and IEEE 14-bus power systems. The SCA's simulation results are compared with the outcomes of Differential Evolution, Genetic Algorithm, Gray Wolf Optimization and Particle Swarm Optimization. This comparison reveals that the SCA’s performance is superior in addressing the ORPD issue.