Document Type

Dissertation

College

College of Engineering

Department

Industrial and Engineering Management

Degree

PhD in Industrial Engineering

Dissertation Defense Date

2025

First Committee Member

Li, Zhaojun

Second Committee Member

Salmon, Christian

Third Committee Member

Ekong, Joseph

Additional Committee Member(s)

Hou, Yu

Abstract

This dissertation addresses this lacuna by proposing a novel non-intrusive load monitoring NILM-integrated load-based GFMI control framework to achieve precise voltage and frequency regulation, as well as harmonic mitigation, thereby enhancing power quality, particularly in the presence of nonlinear and unbalanced loads, fluctuating generation, and reduced system inertia. The proposed method leverages NILM to disaggregate load profiles in real time and extract harmonic features from the iii aggregate load current using an optimized Fast Fourier Transform (FFT) approach, enabling a load-specific real-time model that dynamically adjusts harmonic compensation in GFMI. Through comprehensive simulation analyses, the performance of this innovative approach is validated, demonstrating substantial enhancements in harmonic distortion reduction, voltage stability, frequency regulation, and overall system robustness. This research establishes a foundational framework for the next generation of intelligent, data-driven GFMI, paving the way for adaptive, self-healing smart grids capable of navigating the complexities of the 21st-century energy landscape.

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Available for download on Tuesday, August 25, 2026

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