Decentralized Data-Driven Estimation of Generator Rotor Speed and Inertia Constant Based on Adaptive Unscented Kalman Filter

Tan, Bendong; Zhao, Junbo; Terzija, Vladimir; Zhang, Yingchen

doi:10.1016/j.ijepes.2021.107853

Title: Decentralized Data-Driven Estimation of Generator Rotor Speed and Inertia Constant Based on Adaptive Unscented Kalman Filter

Journal Article · Fri Dec 17 00:00:00 EST 2021 · International Journal of Electrical Power & Energy Systems

DOI:https://doi.org/10.1016/j.ijepes.2021.107853· OSTI ID:1840716

Tan, Bendong; Zhao, Junbo; Terzija, Vladimir;

This paper proposes an online decentralized and data-driven method for synchronous generator rotor speed and inertia estimation. First, an analytical relationship between the generator terminal voltage/current phasors and its internal rotor speed is derived using the Thevenin equivalent. The parameters of the latter are obtained via a recursive estimator, which allows us to estimate the generator's internal rotor speed from voltage/current phasors without the need for any generator information. Second, we reformulate the equivalent swing equation into the Kalman filter form, which enables us to use a priori-estimated internal rotor speed along with measured real and reactive power injections to obtain an estimate of the inertia for each online synchronous generator. This is achieved through an adaptive unscented Kalman filter. We demonstrate that the use of terminal bus frequency to approximate the rotor speed for inertia estimation by existing methods leads to large estimation biases/errors. Numerical simulations carried out on the IEEE 39-bus and Texas 2000-bus systems reveal that our proposed method is consistently more accurate than existing methods. Moreover, our proposed method is insensitive to both the type and location of system disturbances, and it is robust to different levels of measurement noise.

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Research Organization:: National Renewable Energy Lab. (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind Energy Technologies Office (EE-4W)

DOE Contract Number:: AC36-08GO28308

OSTI ID:: 1840716

Report Number(s):: NREL/JA-5D00-81873; MainId:82646; UUID:e35fbc17-15c3-485b-82e6-a27fdf9d0fdf; MainAdminID:63614

Journal Information:: International Journal of Electrical Power & Energy Systems, Vol. 137

Country of Publication:: United States

Language:: English

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