Design and Modelling of Energy Storage Systems for Stability Enhancement of Renewable Energy Integrated AC Microgrids

Introduction: The microgrid is an automated digital grid configured to integrate various renewable energy-supported power stations. The wind energy plant and solar photovoltaic (PV) systems contribute most of the power generation in the microgrid. The microgrid models are associated with the load frequency regulator (LFR) model to suppress frequency oscillation caused by step load and random load dynamics. This research manuscript demonstrates the effectiveness of battery energy storage systems (BESS) and supercapacitors (SC) for improving the stability of an islanded AC microgrid Methods: In a step and random load abnormal scenario, a robust three-dimensional membership function associated grade-II fuzzy fractional PID (GII-FPID) controller is anticipated to suppress frequency error signals and achieve quick frequency stabilisation in the microgrid. Furthermore, to improve frequency stabilisation under step and random load uncertainties, several energy storage devices, such as BESS and SC, are incorporated into the microgrid scenario. The study employs a novel Sinh & Cosh algorithm (Sih-CohA) to develop desired parameters of the GII-FPID controller. Results: It has been found that the proposed Sih-CohA-governed GII-FPID approach effectively handles the uncertainty and is able to enhance the stability of the microgrid system. Discussion: The intelligent action of the anticipated GII-FPID controller has been compared with that of type-II fuzzy PID controllers, universal Fuzzy PID controllers and PID controllers. The optimal action of the Sih-CohA is then examined in relation to the standard SCA and PSO algorithms. Conclusion: It is observed that the suggested GII-FPID approach effectively reduces the settling time of ΔF (frequency error) by 125.32% and 265.98% compared to the Fuzzy PID and PID approaches, respectively.