Data-driven modeling of power system dynamics:Challenges,state of the art,and future work

With the continual deployment of power-electronics-interfaced renewable energy resources,increasing privacy concerns due to deregulation of electricity markets,and the diversification of demand-side activities,traditional knowledge-based power system dynamic modeling methods are faced with unprecedented challenges.Data-driven modeling has been increasingly studied in recent years because of its lesser need for prior knowledge,higher capability of handling large-scale systems,and better adaptability to variations of system operating conditions.This paper discusses about the motivations and the generalized process of datadriven modeling,and provides a comprehensive overview of various state-of-the-art techniques and applications.It also comparatively presents the advantages and disadvantages of these methods and provides insight into outstanding challenges and possible research directions for the future.