A Spectral Clustering Method for Dividing Power Grid Regions Considering Inertia Distribution

With the large-scale integration of high proportion renewable energy into the power grid, the total inertia of the grid has been decreasing year by year, and the inertia distribution of each bus in different regions is uneven. This paper proposes a power system regional partitioning method based on spectral clustering, considering the characteristics of inertia distribution. Firstly, based on the distribution and inertia of synchronous generators in the grid, a node admittance matrix that can calculate the shortest electrical distance is employed; Then, based on the inertia differences of each generator and the shortest electrical distance matrix between them, a normalized Laplacian matrix is constructed using spectral clustering algorithm; Finally, the optimal partitioning of power grid is calculated using the triple index constraints of Calinski Harabasz index, silhouette coefficient, and Davidson index. The simulation results verify the correctness and effectiveness of the proposed method by IEEE 39 node case.