Comparative Study of Sugeno and Mamdani Fuzzy Inference Systems for Virtual Inertia Emulation

Renewable energy sources (RESs) have drawn significant attention due to its several advantages such as clean, cheap, and sustainable energy. The inverter-based RESs invoke undesirable influences such as lowering the entire system inertia and lacking system voltage/frequency stabilization, causing the weakness of system stability and resiliency. This work investigates a novel concept of islanded microgrid utilizing the virtual inertia control-based prominent fuzzy designs (i.e., Mamdani and Sugeno models) to emulate virtual inertia to the system during high RESs penetration, thus augmenting system reliability and resiliency. The efficiency of the Mamdani and Sugeno-based inertia controllers is performed under critical (off-line) operating conditions. In such conditions, the actual system parameters including inertia, governor, and turbine units may change based on time-varying, while the controller still retains the normal values of those units. The results show that, with Sugeno system, the overall microgrid performance demonstrates the robustness in the face of uncertainties during high penetration of RESs/loads and system parameter variations.