Thesis

Complex oscillations in IBR-dominated networks : detection, localization and mitigation

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Awarding institution
  • University of Strathclyde
Date of award
  • 2025
Thesis identifier
  • T17498
Person Identifier (Local)
  • 202193585
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Qualification Name
Department, School or Faculty
Abstract
  • This thesis addresses the critical challenges of identifying and localizing the source of complex oscillations in power network. These mainly originate as a consequence of the abundant proliferation of networks with inverter-based resources (IBRs) and their evolving topologies. This significant emphasis on the IBRs and their participation in modern power grids have significantly changed grid dynamics, making the observability and localization of critical disturbances such as complex oscillations, more challenging. Standard Phasor Measurement Units (PMUs) and Wide Area Monitoring Systems (WAMS) adopted for grid observability face significant limitations in detecting these complex oscillations. This becomes more concerning when the localization of such disturbances depends on devices that are barely able to detect closely spaced, time-varying frequency modes. These oscillations are often caused by control interactions in inverter-based systems, such as Wind Turbine Generators (WTGs), and are amplified by disturbances, faults, and resonance phenomena. To address these challenges, this thesis develops a systematic diagnostic approach for detecting and localizing complex Subsynchronous Control Interactions (SSCI) modes in real-time. A comprehensive review of the literature on oscillation detection methods is conducted, highlighting the need for improved observability and diagnostic tools. The thesis presents a detailed modeling of WTGs, including the dynamics of control loops and their impact on system stability, and provides stability criteria for assessing and analyzing the SubSynchronous Oscillations (SSO) occurrences. A novel approach to overcoming observability constraints using sliding Discrete Fourier Transform (DFT) is explored, followed by the proposal of a new technique using Synchronized Waveform Measurement Units (SWMUs) for time-frequency analysis, enhancing the detection of complex SSCI modes. The research also introduces an innovative methodology for deriving the admittance model at the point of connection (POI), which enables the identification and localization of oscillation sources based on their active/reactive power behavior. The proposed approach is validated through multiple case studies, including the use of synthetic signal testing, real-world data from the northwest China grid, and EMT models of the ERCOT south-region network. Finally, the thesis proposes a novel adaptive control approach for WTGs, integrating a Generalized Hebbian Learning algorithm to enhance damping and prevent oscillations in response to SSR or SSCI events. Simulation results demonstrate the effectiveness and applicability of the proposed methods in real-world scenarios, marking a significant step toward operational solutions that deliver improved grid stability and resilience.
Advisor / supervisor
  • Burt, Graeme
Resource Type
DOI

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