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: steurer@caps.fsu.edu, 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
VabcandIabc
Simulated
Tand
DUT
CHIL
Simulation
Controller
PHIL
Simulation
G
Real Time Simulation
Interface
Interface
Algorithm
Algorithm
MRG
References
References
andFeedback
andFeedback
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
ModelPredictive
Capability
Model
HIL
VandV
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

Pyy 
y
Pyy 
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