Enhancing load frequency control and cybersecurity in renewable energy microgrids: A fuel cell-based solution with non-integer control under cyber-attack

Abstract

The uncertain nature of renewable energy sources (RES) and cyber-attack have become a critical concern in load frequency control (LFC). Attacks on the communication lines of microgrids (MGs) containing critical/sensitive systems are always possible and can disrupt the operation of MGs. To address these challenges, the study focuses on the utilization of hydrogen as a storable energy source to enhance effective LFC in the face of substantial power fluctuations resulting from the uncertainties associated with Renewable Energy Sources. The research investigates a microgrid structure that comprises electrolysis and fuel cell systems, enabling the storage of surplus energy generated by systems utilizing intermittent energy sources, which are expected to become more prevalent in the near future. To illustrate our target, a microgrid structure with RES is modeled by utilizing MATLAB/Simulink with cyber-attack mechanism. In this study, a type 2 fuzzy logic control-based LFC scheme is proposed to reduce frequency deviations caused by potential cyberattacks that may target energy storage systems responsible for ensuring the sustainability of energy in an isolated MG. The primary objective of this study is to achieve optimal LFC in an isolated MG that may be susceptible to both random power fluctuations and potential cyberattacks. The dual-input interval type 2 fuzzy logic controller - fractional order tilt-integral-derivative cascade controller (DIT2FLC-FOTID) has been developed for the LFC of the designed microgrid. The parameters of the FOTID controller are determined through optimization, while the suitable input signal for the FOTID controller is determined using DIT2FLC. The performance of the proposed controller has been examined for various scenarios. In all scenario analyses, the proposed controller consistently demonstrates improvements in the frequency response of the microgrid by over 67% compared to the Fuzzy TID controller, and by over 87% compared to the FOTID controller, across various performance criteria.