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SUB-SYNCHRONOUS RESONANCE ANALYSIS and DETECTION By SUB-SYNCHRONOUS RESONANCE ANALYSIS AND DETECTION By IGOR BRANDÃO MACHADO MATSUO DISSERTATION Submitted in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY IN ELECTRICAL ENGINEERING THE UNIVERSITY OF TEXAS AT ARLINGTON Arlington, Texas, USA December 2019 Copyright by Igor Brandão Machado Matsuo 2019 SUB-SYNCHRONOUS RESONANCE ANALYSIS AND DETECTION By IGOR BRANDÃO MACHADO MATSUO DISSERTATION Submitted in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY IN ELECTRICAL ENGINEERING Committee members: Wei-Jen Lee, Ph.D. (Chair) Ali Davoudi, Ph.D. David Wetz, Ph.D. Ramtin Madani, Ph.D. Rasool Kenarangui, Ph.D. THE UNIVERSITY OF TEXAS AT ARLINGTON Arlington, Texas, USA December 2019 “Be thankful for what you have; you’ll end up having more. If you concentrate on what you don’t have, you will never, ever have enough.” (Oprah Winfrey) ABSTRACT SUB-SYNCHRONOUS RESONANCE ANALYSIS AND DETECTION By IGOR BRANDÃO MACHADO MATSUO, Ph.D. THE UNIVERSITY OF TEXAS AT ARLINGTON Supervising Professor: Wei-Jen Lee With the increasing penetration of renewable generation resources, power grids have become more susceptible to sub-synchronous resonance phenomena, especially to sub-synchronous control interaction, which produces fast-growing oscillations. The power system operation requirements for a reliable, fast and accurate detection and monitoring system for protection and mitigation purposes are increasing. Besides, risk assessment analysis during grid planning and update studies can be extremely time- consuming due to a large number of possible grid configurations and small time-steps required for the simulation of detailed electromagnetic transient (EMT) models. The first part of this dissertation aims to provide an optimized tool for SSR risk assessment analysis based on frequency scanning that uses a multi-frequency signal to estimate the grid impedance at all frequencies with one simulation instead of one simulation per frequency of interest. The technique reduces the effects of nonlinearities normally present in power- electronic-based devices, is based on the harmonic injection method and can be used with black-box models. A case study based on the Texas synthetic grid and with two wind farms and a VSC-based STATCOM was used for the validation of the proposed method, which showed superior accuracy than other studied techniques while being 11.71 times faster than multiple single-frequency injections. The second part of this dissertation provides an SSR detection system based on the power spectrum of the input signal plus frequency, magnitude, and derivative-of-magnitude estimators. All the signal conditioning techniques were also discussed and optimized to enable the detection system to efficiently and accurately work throughout the whole sub-synchronous range (5-55 Hz for a 60 Hz system). Finally, a complete monitoring system from data acquisition to data logging was implemented for the detection system in an FPGA-CPU heterogeneous platform and tested in real-time devices. The system provides several mechanisms to ensure its own reliable operation with several self-monitoring schemes and a health indicator in a dual modular redundancy scheme (primary and backup controller-units). A software-implemented voting scheme then decides which unit will forward all information to the subsystems that will use the output of the detection system. The Texas synthetic grid case was applied to the monitoring/detection system and the detection of sub-synchronous control interaction was observed with pickup times within 10 ms to 40 ms depending on the system disturbance. ACKNOWLEDGMENTS I thank the support of CNPq, National Council for Scientific and Technological Development – Brazil, for the full scholarship for the Ph.D. program. I also thank my advisor, Dr. Wei-Jen Lee, for all directions and knowledge given, and my teammates at the University of Texas at Arlington, Fiacre Iragaba, Farshid Salehi, Long Zhao, and Yuhao Zhou, who were vital during my doctoral program. Also thanks to all committee members, Dr. David Wetz, Dr. Ali Davoudi, Dr. Ramtin Madani, and Dr. Rasool Kenarangui. Finally, I would like to express my gratitude to all members of the EE department of UTA, especially Gail Paniuski, who promptly assisted me so many times. DEDICATION This dissertation is especially dedicated to the memory of my mother, Maluh, who completely supported my pursuit for the doctoral degree, even if it meant we would be 5,000 miles apart. I also especially dedicate it to my father, Nelson, who is my inspiration in both my professional and personal lives. Special thanks to my wife, Livia, who encouraged me and went through all the ups and downs with me on this path; and Marcel (brother), Eric (brother), Claire (niece), and Suzane (sister-in-law) who helped me in all things - great and small. LIST OF FIGURES Fig. 2.1: Series-compensated network with a turbine-generator set. .............................. 17 Fig. 2.2: Equivalent circuit of an asynchronous machine viewed from the stator terminals. ........................................................................................................................................ 20 Fig. 2.3: DFIG connected to a series-compensated network (source of figure: [19] © 2010 IEEE). ............................................................................................................................. 23 Fig. 2.4: Rotor-side converter (RSC) control loops (source of figure: [19] © 2010 IEEE). ........................................................................................................................................ 23 Fig. 2.5: Grid-side converter (GSC) control loops (source of figure: [19] © 2010 IEEE). ........................................................................................................................................ 24 Fig. 2.6: Equivalent circuit of an asynchronous machine viewed from the stator terminals including the voltage drop due to the effect of the proportional gain of the RSC. ......... 25 Fig. 2.7: Equivalent circuit of an asynchronous machine viewed from the stator terminals including the voltage drop due to the effect of the proportional gain of the RSC seen as an equivalent rotor resistance. ........................................................................................ 26 Fig. 3.1: Two sides of a generic grid connected to a POI. .............................................. 33 Fig. 3.2: Scheme of how to apply the frequency scanning tool. ..................................... 34 Fig. 3.3: Typical IGBT current x voltage output characteristic curve (source of figure [44]). ............................................................................................................................... 36 Fig. 3.4: Multisine signal with frequencies 1 Hz apart from 5 Hz to 35 Hz and . ........................................................................................................................................ 37 Fig. 3.5: Wind farm connected to the radial test system. ............................................... 40 Fig. 3.6: Waveforms of the normalized multisine signals using different angles. ......... 42 Fig. 3.7: Total resistance and reactance seen from the POI. .......................................... 43 Fig. 3.8: Error of each method in relation to the reference. ........................................... 44 Fig. 3.9: Time-domain transient simulation results at the POI. Active power on the top. Voltage in the middle. Current on the bottom. ............................................................... 45 Fig. 4.1: DFT of a generic rectangular window. ............................................................ 53 Fig. 4.2: Time-domain and frequency-domain DFT results of the sinusoid with a three- cycle rectangular window. .............................................................................................. 54 Fig. 4.3: DFT of a generic Hanning window. ................................................................. 55 Fig. 4.4: DFT of a generic Hamming window. .............................................................. 56 Fig. 4.5: Generic bandpass filter. .................................................................................... 57 Fig. 4.6: Generic Butterworth lowpass filter. ................................................................. 64 Fig. 4.7: Generic Chebyshev Type I lowpass filter. ....................................................... 65 Fig. 4.8: Generic Chebyshev Type II bandpass filter. .................................................... 65 Fig. 4.9: Generic Elliptic bandpass filter. ....................................................................... 66 Fig. 4.10: Second-order Butterworth filter with passband from 5 to 55 Hz. .................. 78 Fig. 5.1: CPU-FPGA heterogeneous platform................................................................ 81 Fig. 5.2: TMR configuration with a majority voter switch. ........................................... 83 Fig. 5.3: (a) DMR configuration with hardware voter, (b) DMR configuration with software voter (proposed configuration). ....................................................................... 83 Fig. 5.4: An internal clock timekeeper timestamps each sample between GPS synchronization updates, when the skew ∆ is then corrected. ...................................... 84 Fig. 5.5: RAID 10 configuration. ..................................................................................
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