A Survey of Oscillation Localization Techniques in Power Systems

Abstract

With the increasingly high penetration of renewable energy sources and the more integration of flexible loads, the power system is currently experiencing significant changes. While these changes aim to meet the growing needs of modern society, they also lead to the occurrence of more and more power oscillation events. These oscillations could be harmful to the operation of the power system, even causing power outages in poorly damped power systems. Hence, it is important to locate the source of these oscillations in the complicated power system, as control strategies or actions can be taken to mitigate them. To locate the source of oscillations accurately, many efficient techniques for oscillation source localization have been developed in the past decade using different physical properties of the power system and different methods. This survey focuses on these techniques to localize the source of oscillation in power systems. They can be categorized according to the physical metrics used, such as energy, mode shape, traveling wave, and damping torque. They can also be classified according to the specific methods used, such as data-driven, machine/deep learning, and transforms. The principles of these techniques, as well as their advantages and disadvantages, are discussed. Based on this survey, future research challenges on oscillation localization are outlined. The survey aims to provide a comprehensive review of the most existing techniques for oscillation source localization in the literature so that researchers and engineers can identify the most appropriate technique for their respective domains and applications.

Topics & Concepts