Frequency Security Index-Based State of Health Monitoring of a Microgrid Using Energy Storage Systems

In low inertia grids, significant frequency deviations can occur as a result of changes in power (load, generation, etc.), These deviations may activate various protection schemes designed to safeguard the system, potentially leading to blackouts. Therefore, assessing the frequency stability of the power system is crucial. The Frequency Security Index (FSI) serves as a metric for evaluating system stability. However, computing the FSI for a specific load change necessitates actual load changes on the system, which is often impractical. This paper introduces a method for calculating the FSI without requiring load changes for all values. A mathematical expression for the FSI is derived, which uses the values of microgrid parameters (such as inertia and damping constant) to compute the FSI for any load change. Subsequently, the parameters that most significantly affect the FSI are identified. Then, the paper introduces a Moving Horizon Estimation (MHE)-based parameter estimation approach, which leverages small perturbations from an energy storage system to estimate the most influential parameters for the FSI. The results show that the FSI calculation with the estimated parameters is more accurate (compared to COI averaged parameters), enabling a more effective state of health monitoring of the microgrid.