In a deregulated electricity market, managing reactive power is challenging for researchers. Reactive Power Planning (RPP) aims to identify the most efficient configuration for controlling parameters while ensuring compliance with constraints. A new strategy is proposed in this paper for planning VARs in transmission systems. The paper identifies critical nodes for installing surplus VAR support. The line charging factor significantly affects the system’s overall operational expenditure. The Gorilla Troops Optimizer (GTO) algorithm is used to pinpoint the most favorable control parameters to minimize overall operational expenditure while reducing active power losses. The proposed approach is tested on the Indian utility 62 bus test system and demonstrated a 14.36% reduction in overall operational expenditure, proving GTO’s superior performance and versatility in addressing various issues. Numeric and visual results show that the proposed method can obtain satisfactory results in managing the system’s reactive power problem.

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Optimal VAR Support in Competitive Electricity Markets Using Gorilla Troops Optimizer

  • Farha Naz,
  • Saurav Raj

摘要

In a deregulated electricity market, managing reactive power is challenging for researchers. Reactive Power Planning (RPP) aims to identify the most efficient configuration for controlling parameters while ensuring compliance with constraints. A new strategy is proposed in this paper for planning VARs in transmission systems. The paper identifies critical nodes for installing surplus VAR support. The line charging factor significantly affects the system’s overall operational expenditure. The Gorilla Troops Optimizer (GTO) algorithm is used to pinpoint the most favorable control parameters to minimize overall operational expenditure while reducing active power losses. The proposed approach is tested on the Indian utility 62 bus test system and demonstrated a 14.36% reduction in overall operational expenditure, proving GTO’s superior performance and versatility in addressing various issues. Numeric and visual results show that the proposed method can obtain satisfactory results in managing the system’s reactive power problem.