Abstract
This paper presents a new method for detecting power quality disturbances, such as faults. The method is based on the dynamic mode decomposition (DMD) - a data-driven method to estimate linear dynamics whose eigenvalues and eigenvectors approximate those of the Koopman operator. The proposed method uses the real part of the main eigenvalue estimated by the DMD as the key indicator that a power quality event has occurred. The paper shows how the proposed method can be used to detect events using current and voltage signals to distinguish different faults. Because the proposed method is window-based, the effect that the window size has on the performance of the approach is analyzed. In addition, a study on the effect that noise has on the proposed approach is presented.
Highlights
As the power system inertia and stiffness decrease with the growing number of inverter-based energy resources on the grid, the electric grid experiences more variations that impact the power quality (PQ) of the system
Power quality events are more likely to cause system instability with faster transients and larger magnitudes. These power quality events are generally caused at a certain location, such as a fault, solar irradiance variability, load harmonics, or inrush current, and there has been significant interest in detecting the cause and location of the power quality event to quickly diagnose if the event is going to be damaging or allowable
Methods based on Kalman filters (KF) [16], [17], the empirical mode decomposition (EMD) [18], [19], the Teager Kaiser energy operator (TKEO) [20], and the principal component analysis (PCA) [21], [22], have among others been proposed
Summary
As the power system inertia and stiffness decrease with the growing number of inverter-based energy resources on the grid, the electric grid experiences more variations that impact the power quality (PQ) of the system. This paper proposes a DMD-based method that detects whenever a signal exhibits a power quality event. This paper proposes the use of the DMD in a similar manner as the WT, MM, KF, EMD, TKEO, and PCA have been used in the context of analyzing power system signals distorted by a power quality event. It is important to note that the proposed method is intended for signals sampled at high resolutions, above hundreds of kilohertz, that can adequately capture the high frequency phenomena that power systems experience during power quality events. An example of such phenomena are the traveling waves caused by system faults.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
