Real-Time Dynamic Disturbance Estimation of Stand-Alone Microgrids Based on Unknown Input Observer for Frequency Regulation

The frequency stability of stand-alone microgrids (MGs) is highly vulnerable due to the high penetration of fluctuating renewable energy and continuous demand variations that are unknown to the MG in real-time. Therefore, to maintain the frequency of a stand-alone MG within safe operational limits, there should be efficient frequency regulation to correct power imbalances caused by renewable energy systems and demand variations. This paper proposes the application of the unknown input observer (UIO) for dynamic disturbance estimation of unknown inputs in a stand-alone microgrid (MG). The proposed UIO scheme is capable of estimating the internal states of the MG and accurately estimate the disturbances or unknown inputs that affect the steady-state operation of the MG. The robustness of the proposed UIO model is verified for real-time applications using the Speedgoat real-time simulator.