Generator Inertia Estimation in the Frequency Domain Using Ambient Data of the Rotor Speed and Electrical Power

Abstract

This paper proposes a method for estimating an inertia constant of a synchronous generator (SG) from ambient data using its swing equation model, the output of which is the rotor speed. The model inputs are the electrical power and mechanical power. The rotor speed and electrical power are measurable but the mechanical power is unmeasurable. A governor-turbine system of an SG has low-frequency dynamics, which means that a spectral density function (SDF) of the mechanical power deviation is zero at a high frequency region. In this paper, a frequency-domain inertia estimation method is proposed using ambient data of the rotor speed and electrical power. The inertia constant is estimated by curve-fitting SDFs of the ambient data to the transfer function of the model at the high frequency region via a least error squares method. The SDFs are calculated as average periodograms for reduction of their variances. The proposed method is verified by estimating SG inertia in the IEEE 39-bus system.