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<p>This research addressed reactive power planning (RPP) problem as a bi-level optimization problem. In the first level, the study identified susceptible or weak buses where voltage collapse was most likely to occur and in the second level, the optimal settings for shunt capacitors, transformer tap positions and generator VAr limits were obtained. For the weak bus detection, five straightforward techniques viz. Power Flow Analysis (PFA), Line Stability Index (LSI), Voltage Collapse Proximity Index (VCPI), Fast Voltage Stability Index (FVSI), and Loss Sensitivity Analysis (LSA) were employed. The additional shunt capacitor for VAr compensation was mounted on particular buses. These methods collectively provided a comprehensive assessment of the system's susceptibility to voltage instability, aided in proactive measures to enhance network resilience. In the second level, a newly developed metaheuristic hybrid CSAJAYA was proposed to obtain the optimal settings for the aforementioned control variables. The results were compared with well-established algorithms such as Particle Swarm Optimization (PSO), Crow Search Algorithm (CSA), Crow Swarm Optimization (CSO), JAYA and Sine Cosine Algorithm (SCA) to conduct a comprehensive analysis. It was revealed that the FVSI for the IEEE 30-bus system and the LSI for the IEEE 57-bus system provided the best identification of susceptible buses. Also, the superiority and efficacy of the CSAJAYA were established as it outperformed the other algorithms in the comparison for both test systems. This cost-effective solution highlighted the economic advantages of the Optimal Reactive Power Planning (ORPP) problem.</p>

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Metaheuristic techniques and optimal VAr support to the vulnerable buses for improved reactive power planning

  • 期刊论文

  • 发表日期：

    2025年7月27日

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  • Suraj Kumar Rajbhar,
  • Biplab Bhattacharyya

摘要

This research addressed reactive power planning (RPP) problem as a bi-level optimization problem. In the first level, the study identified susceptible or weak buses where voltage collapse was most likely to occur and in the second level, the optimal settings for shunt capacitors, transformer tap positions and generator VAr limits were obtained. For the weak bus detection, five straightforward techniques viz. Power Flow Analysis (PFA), Line Stability Index (LSI), Voltage Collapse Proximity Index (VCPI), Fast Voltage Stability Index (FVSI), and Loss Sensitivity Analysis (LSA) were employed. The additional shunt capacitor for VAr compensation was mounted on particular buses. These methods collectively provided a comprehensive assessment of the system's susceptibility to voltage instability, aided in proactive measures to enhance network resilience. In the second level, a newly developed metaheuristic hybrid CSAJAYA was proposed to obtain the optimal settings for the aforementioned control variables. The results were compared with well-established algorithms such as Particle Swarm Optimization (PSO), Crow Search Algorithm (CSA), Crow Swarm Optimization (CSO), JAYA and Sine Cosine Algorithm (SCA) to conduct a comprehensive analysis. It was revealed that the FVSI for the IEEE 30-bus system and the LSI for the IEEE 57-bus system provided the best identification of susceptible buses. Also, the superiority and efficacy of the CSAJAYA were established as it outperformed the other algorithms in the comparison for both test systems. This cost-effective solution highlighted the economic advantages of the Optimal Reactive Power Planning (ORPP) problem.