Usage
  • 225 views
  • 370 downloads

Modeling, Dynamic Analysis, and Stabilization of Converter-Based Distributed Generation Systems Considering Low-Voltage Ride-Through Requirements, Unbalanced and Weak Grid Conditions, and Load Dynamics

  • Author / Creator
    Mortazavian, Shahed
  • The distributed generation (DG) is an alternative and efficient method to supply electric power to customers in the modern electricity market. Nowadays, there is a growing interest in connecting more DG units to utility distribution networks to satisfy the increasing demand, provide simplified and effective connections, and avoid the high investment costs for system upgrades. For an effective integration of DG units into the power networks, the low-voltage ride-through (LVRT) requirements have been recently recommended for large DG installations. The capability of the LVRT is an important mandate for the converter-interfaced DG units. The system operators impose new grid codes requiring large DG units to remain connected and improve the voltage profile during short-term grid faults. To maintain the stability of the power system, DG units are also expected to inject reactive current proportional to the voltage drop, with a dead-band applied to the voltage deviation.
    This thesis provides a detailed modeling, dynamic analysis, and systematic control design procedure to stabilize the performance of grid-connected voltage-source converters considering LVRT requirements, unbalanced and weak grid conditions, and load dynamics. In this regard, the state-space model of a grid-connected converter (GCC) in dispatchable DG applications and for the power system configuration with single- and multiple-DG units are considered for small-signal stability analysis under unbalanced and low-voltage conditions. Because power distribution systems are naturally unbalanced (due to their lines and loads characteristics, and increasing penetration of DG), such a tool is necessary to realize reliable and secure operation. The state-space model is then used to develop a model-based compensation method that stabilizes the performance of the overall system, especially under a weak grid condition.
    Furthermore, the new LVRT standards require the DG units to not only stay connected to the grid but also inject both positive and negative sequence reactive currents proportional to the unbalanced voltage sag characteristics under severe short-term unbalanced grid faults. In addition to the nonlinear dynamics of a GCC, this requirement adds more coupling and complexity to the system in dynamic, transient and stability studies. Therefore, a multi-stage linearized state-space model, with the consideration of the positive and negative sequence reactive current injection, is developed to analyze the dynamic performance and stability of the GCC-based DG unit under fault conditions. A control design method based on the integrated converter dynamics is also presented to stabilize the converter performance.
    With the expected high penetration level of DG units in modern power distribution systems and recent progress in power converter topologies and ratings, medium voltage DG units will be subjected to a wide range of both static and dynamic loads. Therefore, integrated modeling, analysis, and stabilization approach of a GCC-based DG unit with an induction machine load are studied. A comprehensive multi-stage small-signal model is obtained to provide the possibility of the grid fault studies for different operating states of the system. This model is then used to assess the impact of the induction machine dynamics on the overall system stability as compared with the static load model and under different grid strength conditions. Control design methods to facilitate stable operation and successful LVRT performance are presented and evaluated.
    In all stages of the study, comparative simulation and laboratory-scale experimental results are used to validate the theoretical analysis and the effectiveness of the proposed models and compensation methods.

  • Subjects / Keywords
  • Graduation date
    Fall 2018
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R31Z4286N
  • License
    Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.