Cyberattack‐Resilient Fractional‐Order PPI Control for Frequency Regulation in PV‐Integrated Power Systems

ABSTRACT Load‐frequency control (LFC) comprises a primary process in interconnected electrical power systems, playing a critical role in maintaining the stability and reliability of the electrical grid. It is of paramount importance that the designed controller functions in an optimal manner, particularly with regard to the compression of area frequency and tie‐line power deviations within the scheduled limits. In light of these considerations, this study puts forth the inaugural derivative‐free and delay‐based application of a predictive proportional‐integral (PPI) and its fractional‐order approach (FOPPI) controllers to address the LFC challenge in a PV‐integrated two‐area power system. To attain the most effective controller parameters of the PPI and FOPPI, the artificial rabbits optimisation (ARO) methodology is utilised by aiming to minimise the integral of the time‐weighted absolute error (ITAE) performance measurement. The effectiveness of the proposed FOPPI controller is evaluated through a comparative analysis of existing controller structures in the literature and the classical PPI controller based on reported ITAE values in the literature. The proposed approach is validated through a series of detailed and systematic performance evaluations, such as time‐domain analysis, uncertainty in system parameters, stochastic loading conditions, stability analysis and cyberattack performance of the proposed controllers. Furthermore, a cyberattack detection index for the controllers is considered together with a statistical analysis, and the dataset and simulation models supporting the study are made available as described in the Data Availability Statement. As evidenced by the outcomes of the performance assessments, the FOPPI controller, as conceptualised in this investigation, displays an augmented capacity for dynamic response and resilience in the face of specified scenarios when contrasted with alternative methodologies, including the PPI controller.