Local Measurement Based Robust Voltage Stability Index & Identification of Voltage Collapse Onset

TL;DR

This paper introduces a noise-robust, local static and dynamic voltage stability index (LS-VSI and LD-VSI) that enables real-time, decentralized detection of voltage instability and collapse points using local measurements, validated on multiple power system models.

Contribution

It develops a novel local static-voltage stability indicator (LS-VSI) that avoids Thevenin estimation and a dynamic version (LD-VSI) for early detection of voltage collapse, improving robustness and accuracy.

Findings

LS-VSI is robust to measurement noise and effective on large test systems.

LD-VSI accurately identifies voltage collapse points and instability onset.

Validation on IEEE and real power grid models confirms improved detection capabilities.

Abstract

This paper addresses the problem of real-time monitoring of long-term voltage instability (LTVI) by using local field measurements. Existing local measurement-based methods use Thevenin equivalent parameter estimation that is sensitive to the noise in measurements. For solving this issue, we avoid the Thevenin approach by projecting the power flow equations as circles to develop local static-voltage stability indicator (LS-VSI) that is robust to measurement noises. The proposed method is an attractive option for practical implementation because of its decentralized nature, robustness to noise, and realistic modeling. Next, we utilize LS-VSI to propose a new local dynamic - VSI (LD-VSI) to identify the LTVI triggered by large disturbances and load tap changer dynamics. LD-VSI can identify not only the onset of instability with an alarm but also the voltage collapse point (VCP). Extensive numerical validation comparing LS-VSI with existing methods is presented on IEEE 30-bus and larger test systems like 2000-bus Texas synthetic grid to validate the robustness, accuracy, and situational awareness feature. We also verify the LD-VSI behavior on the Nordic power grid using PSSE dynamic simulation. When compared to existing methods, we observe that LD-VSI is not only more robust to measurement noise but also can identify VCP.