@inproceedings{2df8a8ad1da24f0481ef5ca461fa0306,
title = "Data-Driven Adaptive Damping Controller for Wind Power Plants with Doubly-Fed Induction Generators",
abstract = "This paper presents an adaptive damping controller for wind power plants in which the turbines are equipped with doubly-fed induction generators. The controller is designed to respond to an input control signal that is triggered according to the system operating conditions. A processing unit continuously estimates the electromechanical modes of oscillation based on real-time streaming data acquired from a phasor measurement unit that is strategically positioned on the grid. The decision to trigger (or not trigger) the control signal is automatic, based on the relative damping of the dominant mode. The modes are estimated using the dynamic mode decomposition algorithm with time-delay embedding. Numerical simulations performed on the two-area system demonstrate that the proposed controller enhances the rotor angle stability for both small-signal and large disturbances, and is adaptive to changing grid conditions.",
keywords = "Damping controller, Koopman operator, doubly-fed induction generator (DFIG), dynamic mode decomposition, oscillations, real-time control",
author = "Pranav Sharma and Marcos Netto and Venkat Krishnan and Venkataramana Ajjarapu and Umesh Vaidya",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE Power and Energy Society General Meeting, PESGM 2021 ; Conference date: 26-07-2021 Through 29-07-2021",
year = "2021",
doi = "10.1109/PESGM46819.2021.9638063",
language = "English (US)",
series = "IEEE Power and Energy Society General Meeting",
publisher = "IEEE Computer Society",
booktitle = "2021 IEEE Power and Energy Society General Meeting, PESGM 2021",
address = "United States",
}