Time-Domain Voltage Sag State Estimation Based on the Unscented Kalman Filter for Power Systems with Nonlinear Components

Abstract

This paper proposes a time-domain methodology based on the unscented Kalman filter to estimate voltage sags and their characteristics, such as magnitude and duration in power systems represented by nonlinear models. Partial and noisy measurements from the electrical network with nonlinear loads, used as data, are assumed. The characteristics of voltage sags can be calculated in a discrete form with the unscented Kalman filter to estimate all the busbar voltages; being possible to determine the rms voltage magnitude and the voltage sag starting and ending time, respectively. Voltage sag state estimation results can be used to obtain the power quality indices for monitored and unmonitored busbars in the power grid and to design adequate mitigating techniques. The proposed methodology is successfully validated against the results obtained with the time-domain system simulation for the power system with nonlinear components, being the normalized root mean square error less than 3%.

Keywords

• nonlinear dynamic system
• power quality
• power system simulation
• state estimation
• unscented Kalman filter
• voltage fluctuation