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<p>Load-frequency stability is essential to the reliability of modern interconnected power systems. Robust and adaptive controllers are needed because a disruption in one control area can affect adjacent regions. In a deregulated reheat thermal-nuclear power system, this paper compares traditional PID, fuzzy logic controllers (FLC), and suggested polar fuzzy controllers (PFC). Genetic algorithm (GA) and Cuckoo Search (CS) gain parameter adjustments improve polar fuzzy controller performance. The optimized PFC controller’s frequency deviation, overshoot, settling time, and system resilience are examined under deregulated operating conditions, including Unilateral, Bilateral, and Agreement Violation Transactions. Transient responsiveness and steady-state accuracy are consistently better in simulations for the CS-PFC than for the PID, FLC, and regular PFC. Performance is also examined to assess controller robustness to system parameter uncertainty. This enables consistent and dependable operation even when modelling errors or external disruptions change system parameters. Trapezoidal and Gaussian membership functions are used to study PFC behaviour. The trapezoidal membership function performed better.</p>

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AGC Using Optimized Polar FLC

  • 期刊论文

  • 发表日期：

    2026年6月18日

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  • D. K. Chaturvedi,
  • Shiva Mishra

摘要

Load-frequency stability is essential to the reliability of modern interconnected power systems. Robust and adaptive controllers are needed because a disruption in one control area can affect adjacent regions. In a deregulated reheat thermal-nuclear power system, this paper compares traditional PID, fuzzy logic controllers (FLC), and suggested polar fuzzy controllers (PFC). Genetic algorithm (GA) and Cuckoo Search (CS) gain parameter adjustments improve polar fuzzy controller performance. The optimized PFC controller’s frequency deviation, overshoot, settling time, and system resilience are examined under deregulated operating conditions, including Unilateral, Bilateral, and Agreement Violation Transactions. Transient responsiveness and steady-state accuracy are consistently better in simulations for the CS-PFC than for the PID, FLC, and regular PFC. Performance is also examined to assess controller robustness to system parameter uncertainty. This enables consistent and dependable operation even when modelling errors or external disruptions change system parameters. Trapezoidal and Gaussian membership functions are used to study PFC behaviour. The trapezoidal membership function performed better.