Nodal Inertia Assessment for Renewable Energy Power Systems Based on Vector Fitting Method
The displacement of synchronous generation by converter-interfaced renewable resources erodes system inertia, creating spatial heterogeneity that undermines frequency stability. Existing inertia assessment methods depend on disturbance data, high-quality measurements, or precise models, limiting online deployment. This paper proposes a nodal inertia assessment method based on vector fitting (VF) for renewable energy power systems. A unified assessment framework is established by analyzing frequency response mechanisms of synchronous and renewable generators, incorporating virtual inertia control. An active power-frequency transfer function is constructed for each source node, and its parameters are identified via VF and least-squares fitting. To mitigate the sensitivity of VF to initial pole configuration, particle swarm optimization (PSO) optimizes the initial poles using frequency fitting mean square error as the fitness function. The method is validated on an improved IEEE-39 node system under multiple operating conditions. Results demonstrate significant advantages in assessment accuracy and adaptability, with the PSO-VF approach achieving lower fitting errors than conventional VF. The proposed method enables online nodal inertia monitoring without requiring disturbance information or accurate physical models, supporting optimized frequency control and scheduling in high-renewable grids.