Regional Frequency Measurement Point Selection and System Partitioning Method for High-Renewable-Energy-Penetration Power System

Dongdong Li, Zhenfei Yao, Yin Yao (), Bo Xu and Fan Yang
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Dongdong Li: College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Zhenfei Yao: College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Yin Yao: College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Bo Xu: College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Fan Yang: College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China

Energies, 2025, vol. 18, issue 12, 1-17

Abstract: The integration of high proportions of renewable energy into power systems to replace traditional synchronous generators has led to continuous weakening of the system inertia support and primary frequency regulation resources. Spatiotemporal dispersion of the system’s frequency response has become increasingly prominent. Historical data from numerous frequency disturbance events show that the unified system’s frequency can no longer accurately represent the variations in the frequency response at each node in the system. To address this issue, a method for frequency measurement point selection and system partitioning in a high-renewable-energy-penetration power system is proposed. Firstly, the frequency regulation influence (FRI) index is defined to quantify the comprehensive ability of nodes to dynamically regulate the spatiotemporal dynamics of the power system’s frequency, identifying key frequency regulation nodes as the regional frequency measurement points. Secondly, a hierarchical clustering method is employed to partition the remaining nodes around the frequency measurement points, and the optimal partitioning result is evaluated using modularity indicators. Finally, the effectiveness of the proposed method is verified using a modified standard 39-node system. The simulation results reveal that the proposed frequency measurement point selection and system partitioning method can effectively enhance the accuracy of regional frequency response measurements, as well as the evaluation accuracy of inertia and primary frequency regulation.

Keywords: frequency dispersion; system partitioning; key node identification; hierarchical clustering (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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