English

A Dynamic Response Recovery Framework Using Ambient Synchrophasor Data

Systems and Control 2022-05-09 v3 Systems and Control Signal Processing Optimization and Control

Abstract

Wide-area dynamic studies are of paramount importance to ensure the stability and reliability of power grids. The rising deployment synchrophasor and other sensing technologies has made data-driven modeling and analysis possible using the synchronized fast-rate dynamic measurements. This paper presents a general model-free framework of inferring the grid dynamic responses using the ubiquitous ambient data collected during normal grid operations. Building upon the second-order dynamic model, we have established the connection from the cross-correlation of various types of angle, frequency, and line flow data at any two locations, to their corresponding dynamic responses. The theoretical results enabled a fully data-driven framework for estimating the latter using real-time ambient data. Numerical results using the WSCC 9-bus system and a synthetic 2000-bus Texas system have demonstrated the effectiveness of proposed approaches for dynamic modeling of realistic power systems.

Keywords

Cite

@article{arxiv.2104.05614,
  title  = {A Dynamic Response Recovery Framework Using Ambient Synchrophasor Data},
  author = {Shaohui Liu and Hao Zhu and Vassilis Kekatos},
  journal= {arXiv preprint arXiv:2104.05614},
  year   = {2022}
}
R2 v1 2026-06-24T01:05:20.017Z