State Estimation for Synthetic Inertia Control System Using Kalman Filter

The growing penetration of wind power has deterio- rated the frequency response of power systems, and several meth- ods have been proposed for wind turbines to provide frequency response. Various proposals consider feedback controllers that require measurements of all state variables, and some of th...

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Bibliographic Details
Published in2021 IEEE International Conference on Automation/XXIV Congress of the Chilean Association of Automatic Control (ICA-ACCA) pp. 1 - 7
Main Authors Gutierrez, Fabian, Riquelme, Esteban, Barbosa, Karina A., Chavez, Hector
Format Conference Proceeding
LanguageEnglish
Published IEEE 22.03.2021
Subjects
Conferences
Gold
Integrated circuits
Kalman filter
Linear Matrix Inequalities (LMI)
Synthetic Inertia
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DOI10.1109/ICAACCA51523.2021.9465316

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Summary:The growing penetration of wind power has deterio- rated the frequency response of power systems, and several meth- ods have been proposed for wind turbines to provide frequency response. Various proposals consider feedback controllers that require measurements of all state variables, and some of them are not physically measurable. This work develops a Kalman filter approach via LMI formulation to estimate immeasurable state variables for a wind power synthetic inertia algorithm. A simulation considering different wind speed and wind power penetration scenarios is presented to show numerical results.
DOI:10.1109/ICAACCA51523.2021.9465316