A Method for Real-Time Prediction of the Probability of Voltage Sag Duration Based on Harmonic Footprint

In this paper, a novel method for real-time prediction of voltage sag duration is proposed. It is based on the recently introduced new characteristic of voltage sag, named harmonic footprint, and is formulated using a logistic regression model. The concept is mathematically formulated and statistically analyzed using an extensive set of real grid measurement data which are recorded in distribution grids. Furthermore, the proposed method is applied as a part of an advanced grid-tie converter control. It is included in previously developed methods for fast sag detection and magnitude of voltage sag prediction. The algorithm is applied to the control of grid-tie converters used in distributed generators and tested with real/grid measurement data in the IEEE 13-bus test grid by simulations and in the IEEE 33-bus test grid using a hardware-in-the-loop (HIL) microgrid laboratory testbed. It is shown that this method can prevent unnecessary tripping of distributed generators (DG) and improve low-voltage ride-through (LVRT) support. In addition, the model has the potential to be applied to a wide range of devices or algorithms for the protection, monitoring, and control systems of distribution grids.