The HIL Based Model Validation Paradigm - Tools
Transcription
The HIL Based Model Validation Paradigm - Tools
The HIL Based Model Validation Paradigm - Tools, Challenges, and Application Examples Michael “Mischa” Steurer Leader Power Systems Research Group at FSU-CAPS Email: [email protected], phone: 850-644-1629 39th Annual Conference of the IEEE Industrial Electronics Society Nov 13, 2013, Vienna, Austria Overview • Role of Hardware-inthe-Loop (HIL) • FSU-CAPS 5 MW power HIL (PHIL) facility • De-risking of PHIL experiments • Model Verification and Validation (V&V) • PHIL examples FSU-CAPS High Bay PHIL Lab 2 Basics of HIL Simulation Approach Real Time Simulation • • A device under test (DUT) is interfaced to a simulated environment through HIL interfaces to a real-time simulation model Controller HIL (CHIL) G Power HIL (PHIL) – Power amplifiers and/or actuators are used for interfacing – Full power, high fidelity stimulation • • • DUT to be exercised in a wide range of potentially realistic environments Execution of extreme conditions within controlled lab environment DUT to be tested with systems not yet constructed DISTRIBUTION STATEMENT A: Approved for public release. Distribution is unlimited. MRG DUT Control Simulated – HIL Interfaces use control level (low voltage) signals for I/O • Simulated Signals VabcandIabc Simulated Tand DUT CHIL Simulation Controller PHIL Simulation G Real Time Simulation Interface Interface Algorithm Algorithm MRG References References andFeedback andFeedback A A Amplifier B B C C DUT Dynamometer J. Langston, et.al., “Role of Hardware-in-the-Loop (HIL) Simulation Testing in Transitioning New Technology to the Ship”, in Proc. of IEEE Electric Ship Technologies Symposium (ESTS), April 2013 3 Role of HIL Simulation throughout Technology Development In situ Limited Hardware Testing Relative Effort Power HIL HW only Lab Testing • Modeling and Simulation dominates the entire process • CHIL contributes heavily from proof of concept through PHIL testing – De-risk early development of • Hardware (fast) controller • Application (slow) controller – De-risking PHIL experiments Control HIL • PHIL supports model building and integration phases – Experimental data for model construction and validation – Stimulation of component through controlled transients – Integration testing through emulation of the target environment(s) Modeling and Simulation Proof of Concept Development and Model Building Integration Testing Time 4 FSU Center for Advanced Power Systems • • • • • • • Established at Florida State University in 2000 under a grant from the Office of Naval Research Focusing on research and education related to application of new technologies to electric power systems Organized under FSU VP for Research Affiliated with FAMU‐FSU College of Engineering Lead Member of ONR Electric Ship R&D Consortium ‐ ESRDC ~$8 million annual research funding from ONR, DOE, Industry DOD cleared facility at Secret level Research Groups • • • • • • • Electric Power Systems Advanced Modeling and Simulation Advanced Control Systems Power Electronics Integration and Controls Thermal management High Temperature Superconductivity Electrical Insulation/Dielectrics Staffing • 50 Full‐time staff of scientists, engineers and technicians, post‐doc.’s and supporting personnel • 7 FAMU‐FSU College of Engineering faculty • 45 Students Facility • 44,000 square feet, laboratories and offices, located in Innovation Park, Tallahassee; • Over $35 million specialized power and energy capabilities funded by ONR, DOE Experimental Capabilities • Integrated 5 MW Hardware-in-the-Loop (HIL) testbed – 5 MW variable voltage / variable frequency converter: 4.16 kVac, 1.1 kVdc – 5 MW dynamometers 225/450, 1,800/3,600; -12,000/24,000 RPM – 5 MW MVDC converters: 6/12/24 kV – Real-time Digital Simulators (RTDS, OPAL-RT) • <2 μs step in real-time – Cyber-physical system simulation in RT • Superconductivity and crogenics – AC Loss and Quench Stability Lab – Cryo-dielectrics High Voltage Lab – Cryo-cooled systems lab • Low power and smart grid labs FSU-CAPS PHIL Test Facility Fully Integrated with Real-Time Simulator NEW – 4 x MMC converters Delivered : Oct 28, 2013 Substation SCC 800 MVA @ 12.5 kV B1 12.47 kV B3 B2 4.16 kV Exp. Bus (Port) B4 Future Feed T1 7.5 MVA, 5% Future B15 Future Feed SP2 SP4 4.16 kV S10 S4 ~ S5 T6 C1 C2 ~ = = = = = = ~ = = 0.8 MW PCM4 4.16kV / 1 kV (DC) ~ = M2 = = DC Bus T10.1 ~ T10.2 B14 M1 ~ MVDC Experimental Bus Parallel: 6 kV, 0.8 kA, Series: 24 kV, 0.21 kA ~ = ~ = T9.2 C4 ~ = ~ T9.1 ~ ~ ~ B12 B6 T7 ~ B13 S8 B5 3.5 / 4.16 kV SP 5 MW Max PHIL…Power Hardware in the Loop SS1 SS3 500-1150 VDC 1.5MW @ 600VDC 2.8MW @ 1150VDC 5 MW VVF AC Bus 4.16 kV Exp. Bus (Starboard) S 1.5 MVA 480 V bus PHIL Challenges Accuracy, Stability, Protection • Real-time simulation – Fixed time-step with minimum achievable time-step size – Limitations on the size and complexity of simulated systems Device Under Test – Protection of experiment • Amplifiers, Actuators – Limited bandwidth – Time delays – Maximum power, torque, speed, etc. – Availability of RT model DUT Controller Flexible Protection of experiment Amplifier Amplifier Controls Interface Component PHIL Interface Controls Rest of System Real Time Simulator PHIL Interface • Interface Algorithms – Application specific – Ensures stability of PHIL setup • Availability of DUT model for de-risking and tuning of protection • Accuracy of models used for surrounding systems (rest-of-system - ROS) – Common issue – establishing confidence in the models 4/2013 8 De-risking: CHIL Simulation of 5 MW “Amplifier” Flexible Protection of experiment Device Under Test Amplifier DUT Controller Amplifier Controls Interface Component PHIL Interface Controls Rest of System Real Time Simulator PHIL Interface 06/26/2007 9 Simulated PHIL Experiment Real Time Simulator Device Under Test Amplifier DUT Controller Amplifier Controls Flexible Protection of experiment Interface Component Hardware in Lab Device Under Test DUT Controller PHIL Interface Controls Amplifier Amplifier Controls Rest of System Real Time Simulator Transition between modes for every change in the experimental setup 10 Model Verification and Validation Vr • Quantitatively Assess the predictive capability of models. • Identify – – – – V src A Lsrc Ia Va B Idc P Ib Vb C Vr A V dc B Rload Ic Vc C N Active AC/DC Rectifier Surroundings Scenarios Observable Quantities Response Quantities DUT Voltage • In order to be of value, these must be carefully selected • By standardizing for common classes of components, improve quality of results Vmax Tsettle Time DISTRIBUTION STATEMENT A: Approved for public release. Distribution is unlimited. J. Langston, et.al., “Role of Hardware-in-the-Loop (HIL) Simulation Testing in Transitioning New Technology to the Ship”, in Proc. of IEEE Electric Ship Technologies Symposium (ESTS), April 2013 11 Synergy Between Verification and Validation and HIL Simulation • • • • HIL can facilitate economically carrying out validation experiments on the DUT HIL simulation test plans can be based around scenarios for V&V (including surrounding system models, scenarios, response quantities, etc.) Results can be used for improvement/calibration of DUT models and/or for assessment of prediction error with models HIL simulation experiments can be employed at various stages of the development process (using CHIL for testing controllers, etc.) Definitions of Surroundings, Scenarios, and Response Quantities Simulation Models of Suroundings ModelPredictive Capability Model HIL VandV Simulation Experimental Data HIL community needs V&V guidelines and “standards” DISTRIBUTION STATEMENT A: Approved for public release. Distribution is unlimited. J. Langston, et.al., “Role of Hardware-in-the-Loop (HIL) Simulation Testing in Transitioning New Technology to the Ship”, in Proc. of IEEE Electric Ship Technologies Symposium (ESTS), April 2013 12 Megawatt Scale High-Speed Generator RTDS Trigger/Synch Voltage -+ Voltage/ Current/ Duty Cycle Open/Close Measured Quantities Voltage DAQ Speed Current Speed/ Torque Rectifier VVS Generator Gearbox Dyno ~ 1.8 1.6 1.6 MW in 400 ms 1.4 1.2 Moved from Model to CHIL to full-scale PHIL • Offline models used nano-second time step • Startup, shutdown procedure • Steady-state and dynamic loading (ramping) Actual Reference 1 0.8 0.6 0.4 0.2 0 -0.2 4/2013 0 0.1 0.2 0.3 Time (s) 0.4 0.5 0.6 funded by 13 Dynamic HIL Testing of Large Inverters Substation 6.3 MVA Variable Voltage Source (VVS) B1 B2 T1 B15 Real Time Simu lator RTDS 4.16kV S10 B13 T9.1 VVS 1 T9.2 ~ PV Array Simulation = = = = Real Time Simu lator RTDS VVS 2 ~ DC Bus: 0-1150VDC I max = +/- 2.5 kA = ~ = PV Inverter ~ Power Grid Simulation 466/4160V 3.93MVA Z=5.6% T10.1 B14 4.16kV AC Bus AC Bus1: 0-4.16 kV I max = 0.433 kA 4/2013 T5 B11 PHIL testing of MW-scale converters is possible today! Low voltage ride through Fault current contribution Unbalanced voltage Anti-islanding up to 1.5 MW AC Bus2: 0-0.48 kV I max = 1.8 kA 4160/480V 1.5MVA Z=5.86% funded by 14 Inverter with 0.8 PF lagging 0.22 Voltage (kV) Vsim Vm Vr 0.21 Im = 0.2 1 ~ 2 3 Active Power (MW), 0.5 Reactive Power (MVAR) V 4required to 5 drive reactive Time (min) current through T5 6 T5 2 3 B11 Psim Pact Qsim Qact 0 -0.5 1 4 Time (min) 5 Vm 7 6 4 Z Vr 7 Simulated grid impedance X < XT5 See J. Langston, et al. “Power Hardware-in-the-Loop Testing of a 500 kW Photovoltaic Array Inverter”, in Proc. of IECON, Montreal, Canada, 2012 4/2013 15 PHIL testing of SiC converter 4.16 kVAC-1 kVDC B13 AC side 4.16 kV DC side • Simulates surrounding system (sources, loads) • Provides ultra-fast protection T9.1 385 V T9.2 RTDS ~ ~ = = ~ VVS 1 ~ ~ = = ~ = Voltage Ref (Vab (t), Vbc (t)) Voltage & Current Fdbk Voltage & Current Fdbk Current Ref (duty cycle) ~ ~ = 0…466 V 0…4160 V 438 A max (cont.) 45 Hz – (approx.) 100 Hz Small signal bandwidth limit approx. 1 kHz VVS 2 = 0…1150 V 2.5 kA max 0…approx. 100 Hz Small signal bandwidth limit approx. 1 kHz T10.1 B14 = Device under test funded by 16 Concluding Remarks • PHIL testing is advancing rapidly – A tool to address several challenges associated with transitioning technology (de-risking) – Emulate a wide range of surroundings and scenarios, simulate yet unrealized systems • Impact of PHIL interface more pronounced at MW scale experiments – Aim for close coupling between reference and amplifier but acknowledge the limitations in the simulated PHIL setup – Develop affordable faster switching amplifiers – Improve real time simulation of models – Proper model construction and validation is key to success Team at work in FSUCAPS control room • Simulation based preparation of MW scale experiments expected to save time and money – Improve development cycle – Discover hidden issues early • Need to develop common guidelines and “standards” to accelerate adoption of HIL paradigm 4/2013 500 kW PV converter in FSU-CAPS lab 17 • http://www.caps.fsu.edu/documentcontrol.html V&V: Quantification and Assessment of Model Predictive Capability Numerical Uncertainty X Simulation Pyy y Pyy o x2 o o x o o Error x1 y Prediction Err x In order to provide confidence bounds on predictions, combine • model uncertainty • numerical error • predicted model form error into prediction at untested operating point DISTRIBUTION STATEMENT A: Approved for public release. Distribution is unlimited. J. Langston, et.al., “Role of Hardware-in-the-Loop (HIL) Simulation Testing in Transitioning New Technology to the Ship”, in Proc. of IEEE Electric Ship Technologies Symposium (ESTS), April 2013 19 DC-side: Photovoltaic Emulation 1.6 Current (kA) 0.4 0.5 Maximum power point 0.7 1.4 0.6 1.2 0.5 1 0.4 0.8 0.3 0.6 0.2 0.4 0.1 0.2 0 0 -0.05 0.3 Power (MW) 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 -0.1 0.0 0.1 0.2 Voltage (kV) 0.30 4/2013 0.32 0.34 0.36 0.38 Voltage (kV) 0.40 Ensure that DC-amplifier controls allow PV-emulation in conjunction with PV inverter dynamics. 20 Grid-side PHIL Interface Model/Simulation PCC Simulated Feeder Vmag‐sim Filter PI Controller + Σ Filter Controller VVS Voltage Magnitude Reference ‐ • Choice: Voltage Current, but impacts stability • Know your limits: Filters for bandwidth adjustment Equipment RTDS Hardware Vmag Currents Voltage Id, Iq PV Inverter TransTransT5 former former AC VVS • Protect: Open loop operation through feedback gain adjustment Device under Test 4/2013 21 Cyber-Physical RT Simulation RT simulation of Controls Communications Distributed Controls (DC) computing layer Fast data links between DC and power components: RT simulator specific RT simulation of electric power system