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This study designs an effective mitigation control scheme for a class of attacks called resonance attacks on the power grids. Mainly in this attack, an enemy is able to disturb a stable power system via manipulation in rate of change of frequency (RCF). Thus, in countermeasures, a detection and mitigation control scheme propose using artificial neural network (ANN) observer-based sliding mode controller (SMC) in this study. Malicious resonance offensive uncertainties are estimated via ANN observer effectively. The estimated states and uncertainties via ANN observer are utilized as input in SMC design to select switching surface boundary limits. The asymptotic stability of proposed control scheme is analysed using the Lyapunov stability theorem. The presented control technique regulates rate of change of frequency within permissible limits with reduction in chattering and frequency oscillations even in presence of resonance offensive patterns. Detection and mitigation capability of proposed controller is illustrated by MATLAB simulations.

Resonance attacks detection and mitigation control scheme on frequency regulation in multi-area smart grid