Evaluating power system network inertia using spectral clustering to define local area stability

The transitioning from synchronous machine generation to large-scale integration of inverter-based renewable generation introduces new challenges in power system frequency stability. This paper proposes a new approach for evaluating power system frequency stability based on network clusters. First, the most common metrics for power system frequency stability are presented, with their advantages and disadvantages. Then, we establish the link between frequency response and network topology. Based on the pros and cons of current frequency stability metrics and the influence of network topology, a proposal is made for a new approach to evaluate frequency stability using Spectral Graph Theory to partition a power system network into clusters for analysis. Consider the displacement of synchronous generator inertia, together with the spatial-temporal fluctuations/noise fed in from spatially distributed variable renewable energy sources. Then the proposed clustering approach has two main advantages over traditional methods for evaluating power system frequency robustness. The first is a spatial awareness of a power system network in terms of frequency-stable areas. The second advantage is the ease of interpretation of the metric result for robust network planning.

Automated summary

This paper proposes a new approach for evaluating power system frequency stability based on network clusters. By partitioning the power system network into clusters for analysis, it achieves an evaluation of frequency stability with spatial awareness and easy interpretation of metric results.