Doctoral Dissertations

Date of Award

8-2025

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Electrical Engineering

Major Professor

Yilu Liu

Committee Members

Fangxing Li, Jin Tan, Yi Zhao

Abstract

The shift to high renewable power grids has significantly challenged grid reliability and stability due to the replacement of traditional generators with inverter-based resources (IBRs), which lack inherent inertia and rely on hard-to-quantify virtual inertia contributions. This reduction in system inertia heightens the risks of frequency deviations and inter-area oscillations, necessitating real-time inertia estimation software and Wide Area Oscillation Damping Controllers (WADCs). Furthermore, the enormous increase in the amount of large voltage-sensitive-load in modern grids, such as AI data centers, exacerbate these challenges through rapid load swings, oscillation risks, and instability during faults or reconnections. Addressing these issues requires advanced real-time stability analysis tools and improved data center load modeling to mitigate their impact on modern, low-inertia grids.

This doctoral dissertation proposes several contributions: (a) Developed a probing-based real-time system inertia estimation tool and validated its estimation performance through both power-hardware-in-loop (PHIL) test and Kauai Island field demonstration. (b). Developed an adaptive wide-area damping controller (WADC) for large-scale power grids with capability to handle different communication uncertainties. Validated its damping performance through both hardware-in-loop (HIL) test and Italy power grid field demonstration. (c). Developed machine learning (ML) based power system stability assessment tool. Implemented two machine learning models for frequency nadir prediction and critical clearing time (CCT) prediction that can handle grid topology changes. (d). Conducted data center load modeling study in EI grid. Use CMLD composite load model to model general data centers and conduct CMLD parameter study to better parameterize data centers loads. Applied data center loads to MMWG EI grid model and study data center load’s fault responses. (e). Conducted a forced oscillation frequency sensitivity analysis with a specific focus on the resonance condition. Used a frequency scanning approach to analyze forced oscillation sensitivity across three power systems: Kundur, real utility based ERCOT, and MMWG EI models.

Download
Files over 3MB may be slow to open. For best results, right-click and select "save as..."

Share

COinS