Innovative Load Frequency Control: Integrating Adaptive Backstepping and Disturbance Observers

Abstract

Load frequency control (LFC) in large interconnected power systems is crucial for balancing electricity supply and demand while minimizing frequency deviations. Traditional methods like proportional-integral-derivative (PID)controllers and advanced techniques such as evolutionary algorithms and artificial intelligence (AI) have limitations, including computational complexity, sensitivity to parameter changes, and high resource demands. This paper introduces a novel decentralized observer-based backstepping control (DOBC) strategy to overcome these challenges. In our work, each area controller utilizes local measurements and feedback signals to regulate its own area frequency. This approach inherently reduces the reliance on centralized communication and minimizes the impact of potential communication failures, such as packet losses and delays. The proposed method synergistically combines backstepping and disturbance observer techniques, resulting in rapid and stable system responses with reduced control effort, while a noncertainty equivalent adaptive approach ensures exponential disturbance estimation and maintains system stability under time-varying disturbances. Unlike conventional sliding mode control, the proposed method eliminates chattering, making it suitable for sensitive applications. Simulations validate its effectiveness under time delays, parametric uncertainties, nonlinearities, and load disturbances. Results show superior transient response, better oscillation damping, and lower control effort compared to adaptive neuro-fuzzy inference system based fractional-order PID-acceleration controller (ANFIS-FOPIDA), Second-Order sliding mode control (SOSMC), and Deep Reinforcement Learning (DRL). The paper concludes with a rigorous stability and robustness analysis, demonstrating the method’s resilience to parametric uncertainties and time-varying disturbances. This highlights its practical applicability and advantages in modern power systems.