Abstract
This paper proposes a decoupled wide-area damping controller (WADC) leveraging adaptive unscented Kalman filter (UKF) approach. Initially a modal optimal output feedback (MOOF) technique is employed to extract decoupled single-mode feedback signals, which requires only simple gains to dampen IAOs. The decoupling facilitates the distribution of the control effort through the active power output of power injection sources (PISs). Extracted single-mode feedback signals are estimated in real-time using adaptive UKF and phasor measurement unit (PMU) data. The adaptive UKF dynamically updates the measurement and process noise covariance matrices, ensuring reliable estimation in uncertain scenarios. Finally, an interacting multiple model (IMM) approach is employed to adjust control strategies for operating point uncertainties due to low inertia intermittent renewable energy sources (RESs), changes in loading conditions, and time delay in the feedback signals, etc. The proposed methodology is validated on wind farm-integrated IEEE benchmark 4-machine 11-bus system and 16-machine 68-bus system. The decoupled WADC strategy enables simple and effective control modulation across different PISs, while the proposed adaptive UKF estimates single-mode feedback signals even in the presence of unknown covariance matrices.
| Original language | British English |
|---|---|
| Pages (from-to) | 29-43 |
| Number of pages | 15 |
| Journal | IEEE Transactions on Power Systems |
| Volume | 41 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- decoupled control
- dynamic state estimation
- Inter-area oscillations
- unscented Kalman filter
- wide area damping controller
- wind turbine system
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