Robust estimation of power quality disturbances using unscented H∞ filter

• Derivative free adaptive filtering based on unscented transformation.
• State space model using state variables and generation of sigma points for power quality estimation.
• Better tracking of power quality disturbances as compared to unscented Kalman filter (UKF).
• Minimum MSE as compared to RLS, EKF and UKF during estimation of harmonics and other power quality disturbances.

This paper proposes a novel adaptive filtering method for tracking the power quality disturbances present in distorted power signals. The proposed filter known as unscented H∞ filter (UHF) is the robustification of unscented Kalman filter (UKF) and is based on state space modeling. The performance of unscented H∞ filter has been compared with other adaptive filters considering signals, which can represent worst case measurement and network conditions in a typical power system. State space modeling is used to estimate power quality disturbances like sag, swell, notch in presence of additive white Gaussian noise (AWGN). Also the amplitudes and phases of different harmonics under high noisy conditions and decaying DC are also estimated which shows the robustness of the filter. Comparison results demonstrate that under identical conditions, the performance of UHF is better compared to UKF.

(1) Derivative free adaptive filtering approach using unscented transformation. (2) Robust power quality estimation. (3) Tracking higher order harmonics.Figure optionsDownload as PowerPoint slide