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1 Chapter 6: Real-Time Digital Time-Varying Harmonics Modeling and Simulation Techniques Contributors: L-F. Pak, V. Dinavahi, G. Chang, M. Steurer, S. Suryanarayanan, P. Ribeiro Organized by Task Force on Harmonics Modeling & Simulation Adapted and Presented by Paulo F Ribeiro AMSC May 28-29, 2008
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2 Need for Sophisticated Tools for Power Quality (PQ) Studies Proliferation of nonlinear and time-varying loads has led to significant power quality concerns. Traditionally, time-varying harmonics were studies using statistical and probabilistic methods for periodic harmonics. Cannot describe random characteristics Cannot capture the reality of physical phenomena. A time-dependent spectrum is needed to compute the local power-frequency distribution at each instant. Significant advances in equipment for PQ monitoring, waveform generation, disturbance detection, and mitigation. Digital signal processing is widely used. Sophisticated power electronic controllers are used for PQ mitigation. Need for testing and validation of such equipment. Real-time digital simulation as an advanced tool for PQ analysis and mitigation.
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3 Real-Time Harmonic Modeling and Simulation Techniques Wave Digital Filters Discrete Wavelet Transform Real-Time Electromagnetic Transient Network Solution Real-Time Digital Simulators RTDS PC-Cluster Based Simulators HYPERSIM DSPACE
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4 Wave Digital Filters Digital Signal Processing tool that transforms analog networks into topologically equivalent digital filters Synthesis is based on wave network characterization Designed to attain low-sensitivity structures to quantization errors in digital filter coefficients Powerful technique for simulating power system harmonics and transients
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5 Discrete Wavelet Transform Time-Frequency representation of time varying signals. Wavelet analysis starts by adopting a prototype function. Time Analysis is done with a contracted high-frequency prototype. Frequency analysis is done using a dilated low- frequency prototype. Operator representation theory is used to model electrical componenets in discrete wavelet domain
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6 PC-Cluster Based Real-Time Digital Simulator Real-Time eXperimental LABoratory (RTX-LAB) at the University of Alberta.
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7 Fully Flexible and scalable Fast FPGA based analog and digital I/O and high intra-node communication speed Varity of synchronization options Compatible with MATLAB/SIMULINK and other programming languages Features of the RTX-LAB Simulator
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8 Two types of computers- Targets and Hosts Targets are dual CPU based 3.0 GHZ Xeon, work as the main simulation engine and facilitates FPGA based I/Os Hosts are 3.00 GHZ Pentium IV, used for model development, compilation and loading of the model to the cluster Hardware Architecture of the RTX-LAB Simulator
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9 Software Architecture of the RTX-LAB Simulator Target OS- RedHawk Linux Host OS- Windows XP Model Development- MATLAB/SIMULINK Other programming Languages C, C++
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10 InfiniBand Link Maximum Throughput- 10Gbps Shared Memory bus speed – 2.67Gbps Signal Wire Link Data Transfer rate-1.2Gbps Gigabit Ethernet link Transfer Rate- Up to 1Gbps I/O signals from real-hardware are connected through FPGA based I/Os Xilinx Virtex-II Pro is used 100 MHZ operation speed Communication Links in the RTX-LAB Simulator
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11 Subsystems and Synchronization in the RTX- LAB Simulator
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12 Case Study 1: Time-Varying Harmonic Analysis on the RTX-LAB Real-Time Digital Simulator Single-line Diagram of the Arc Furnace Installation
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13 Case Study 1: Time-Varying Harmonic Analysis on the RTX-LAB Real-Time Digital Simulator Schematic of the Arc Furnace Model
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14 Case Study 1: Time-Varying Harmonic Analysis on the RTX-LAB Real-Time Digital Simulator Voltage and Current for the Arc Furnace
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15 Case Study 1: Time-Varying Harmonic Analysis on the RTX-LAB Real-Time Digital Simulator Voltage at the Primary Winding of the MV/LV Transformer
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16 Case Study 1: Time-Varying Harmonic Analysis on the RTX-LAB Real-Time Digital Simulator Current in the Primary Winding of the MV/LV Transformer
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17 Provides time domain solution in real time with typical time step sizes around 50 μs using the Dommel (EMTP) algorithm Features dual time step (<2 μs) capability for PE simulations Allows up to 54 electrical nodes per rack, but subsystems can be connected through cross-rack elements (transmission lines, etc.) Large library of power system and control component models (like EMTDC) > 350 parallel DSPs > 2500 analog outputs and over 200 digital inputs and outputs RPC – Network Solution IRC – Inter-rack Communication WIF – Workstation Interface 3PC – Controls, system dynamics GPC – Network solution, fast-switching converters RTDS at CAPS
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18 Largest RT simulator installation in any university worldwide Systems of up to 250 three-phase buses Sufficient high-speed I/O to enable realistic HIL and PHIL experiments 14 Rack RTDS Installation at CAPS
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19 (Controller) hardware in loop (HIL) and power hardware in loop PHIL Simulated rest of system
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20 Case Study 2: Power Quality Sensitivity Study of a Controller on the RTDS Schematic of the Industrial Distribution System and Rectifier Load
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21 Case Study 2: Power Quality Sensitivity Study of a Controller on the RTDS Single-phase Voltage Sag (40% reduction, no phase shift) and its Impact on Rectifier DC Output
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22 Case Study 2: Power Quality Sensitivity Study of a Controller on the RTDS Phase-Shifted Single-phase Voltage Sag (40% reduction) and its Impact on Rectifier DC Output
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23 Voltage (kV) Case Study 3: Harmonic Distortion on the RTDS Shipboard Power System
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24 Case Study 4: A HIL Simulation for Studying the Transient Behavior of Wind DG
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25 Case Study 4: A HIL Simulation for Studying the Transient Behavior of Wind DG
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26 Conclusions With rising number of time-varying and nonlinear loads sophisticated harmonics modeling and simulation tools are needed. A combination of fast topological methods and powerful real-time simulators can overcome limitations of off-line simulation tools. A general review of current off-line harmonic modeling and simulation tools is presented. Currently available real-time simulation techniques are discussed. Two real-time case studies: arc furnace modeling and power quality sensitivity of a controller, are presented.
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