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An Optimised Adaptive Integral Sliding Mode Control Approach for Multi‐Area Power Systems: Enhancing LFC Robustness and Stability With RES Integration and Time‐Delay Mitigation

Tushar Kanti Roy, Sajeeb Saha, Amanullah Maung Than Oo

2025IET Energy Systems Integration11 citationsDOIOpen Access PDF

Abstract

ABSTRACT Frequency stability is vital to power system operation, especially in interconnected power systems (IPS) and smart grids where renewable energy sources and load fluctuations introduce unpredictability. This variability and time delay from decentralised control configurations can impair load frequency control (LFC) and compromise system stability. This study proposes a robust adaptive integral terminal sliding mode controller (RAITSMC) for LFC to address these challenges. The controller mitigates destabilising effects from time delays, parametric uncertainties and nonlinear disturbances. A delay‐dependent sliding surface is developed to enhance the system's response to tie‐line power and frequency deviations. Perturbations are estimated using an adaptation law, and a decentralised robust control law ensures the system's trajectory remains on the sliding surface with minimal control efforts. The controller's stability is validated via the Lyapunov theorem, and its parameters are optimised using the arithmetic optimisation algorithm. Simulations on the IEEE 10‐generator New England 39‐bus power system demonstrate significant improvements, including reduced frequency overshoot (48.3%), undershoot (45.7%) and settling time (37.2%), along with enhanced robustness under 50% parametric variations. Comparative analyses reveal superior performance across error‐based indices, showcasing RAITSMC's potential to ensure a reliable and stable power system operation.

Topics & Concepts

Integral sliding modeControl theory (sociology)Robustness (evolution)Stability (learning theory)Electric power systemRobust controlControl engineeringComputer scienceSliding mode controlEngineeringPower (physics)Control (management)Control systemPhysicsElectrical engineeringNonlinear systemBiochemistryChemistryGeneQuantum mechanicsArtificial intelligenceMachine learningFrequency Control in Power SystemsMagnetic confinement fusion researchPower System Optimization and Stability