A New Generator Clustering Approach for Power System Inertia Estimation with Reduced Number of Frequency Monitoring Nodes

Large-scale displacement of synchronous generators by renewable energy (RE) sources leads to diminishing power system inertia. Low system inertia makes the system more vulnerable to a higher rate of change of frequency and frequency deviations following an infeed loss, thus forcing the system operators to estimate and monitor system inertia during high RE penetration. However, for system inertia estimation, monitoring frequency dynamics across the power system is one of the main challenges as installing an adequate number of frequency monitoring devices is economically not feasible. In this backdrop, a new inertia estimation approach using a reduced number of optimally identified frequency monitoring nodes, yet with a higher accuracy estimate has been proposed in this paper. The electrical distances between different generators in the system obtained by using synchronizing power coefficient data has been considered to cluster generators to split the whole power system into frequency control zones. Therefore, in the proposed method, a reduced number of frequency measurements from different clusters is used to accurately estimate the system inertia. The proposed approach of system inertia estimation has been implemented and validated on IEEE 39 bus system developed in DIgSILENT PowerFactory simulation platform.