Ambient-Data-Driven Modal-Identification-Based Approach to Estimate the Inertia of an Interconnected Power System

Abstract

A novel approach for estimating the inertia of an interconnected power system is presented using the identification of interarea oscillation modes (frequency, damping and mode shape) extracted from ambient data. The proposed method concentrates on estimating the values of the effective inertia of each area rather than the equivalent inertia of the entire system. Based on an equivalent two-machine system (ETmS) obtained by combining small signal stability analysis (SSSA) with the structure of the power grid, we derive a mathematical relationship between the effective inertia of each area and the interarea oscillation modes. Furthermore, the interarea oscillation modes can be extracted from ambient data, and the developed scheme enables an online estimation of the inertia only by using the outputs measured by PMUs. The performance of the proposed methodology is tested via numerical simulation cases and real data.

Keywords

• Inertia constant
• small signal stability analysis
• modal identification
• ambient data
• interconnected power system