Grid Frequency Estimation based on Extended Kalman Filter in Connected AC Microgrids

The lack of rotational inertia requires fast action for frequency control, thus measurements delays can create instabilities or make the controller ineffective. This is a challenge for grid-connected Microgrids whose frequency requires to be adequately monitored and maintained under operationally margins. Generally, in a power system, the strongest generators are the ones capable of maintaining the frequency of the system, however, when having distributed resources it is harder to keep such frequency between a secure threshold. Therefore, estimating frequency values in a short period of time becomes a helpful feature in this new structure of power systems. This work discusses the Extended Kalman Filter (EKF) application for grid frequency estimation in AC connected microgrids by using a simple second order model. Furthermore, the EKF is used for forecasting the nadir according to the sample time variation. A microgrid benchmark is developed and tested under several load scenarios to test the frequency estimation process.