Dynamic Response Recovery Using Ambient Synchrophasor Data: A Synthetic Texas Interconnection Case Study

TL;DR

This paper introduces a model-free method to infer power grid dynamic responses using ambient synchrophasor data, validated through a synthetic Texas system case study, enhancing real-world grid stability analysis.

Contribution

It presents a novel framework for recovering dynamic responses from ambient data, surpassing frequency-only methods and applicable to realistic power system models.

Findings

Angle data outperforms frequency data in dynamic modeling

Method works with nonlinear, higher-order dynamics

Validated on synthetic Texas Interconnection data

Abstract

Wide-area dynamic studies are of paramount importance to ensure the stability and reliability of power grids. This paper puts forth a comprehensive framework for inferring the dynamic responses in the small-signal regime using ubiquitous fast-rate ambient data collected during normal grid operations. We have shown that the impulse response between any pair of locations can be recovered in a model-free fashion by cross-correlating angle and power flow data streams collected only at these two locations, going beyond previous work based on frequency data only. The result has been established via model-based analysis of linearized second-order swing dynamics under certain conditions. Numerical validations demonstrate its applicability to realistic power system models including nonlinear, higher-order dynamics. In particular, the case study using synthetic PMU data on a synthetic Texas Interconnection (TI) system strongly corroborates the benefit of using angle PMU data over frequency data for real-world power system dynamic modeling.