Transcript CAPS_ESRDC_26May2009_Overview

ESRDC
FSU – CAPS
2009 ESRDC Team Meeting
At
Mississippi State University
2009 ESRDC Team Meeting, 26-27 May, MSU
ESRDC FSU-CAPS Stats
• ESRDC FSU-CAPS Team
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Co-PIs:
Full Time Scientists :
Post Doc:
PhD Students:
MS Students:
Undergrad Students:
Engineers:
Technicians:
Nine
Five
Seven
Eleven
Nine
Seven
Four
Five
2009 ESRDC Team Meeting, 26-27 May, MSU
2
A Reconfigurable Power Quality Regulation
System with Energy Storage Element
Dr. Liming Liu (Scientist), and Dr. Hui Li (PI), CAPS, Florida State University
Proposed reconfigurable power quality regulation system topology
PCC
Udc1
S1
S3
ZS
is
Lf1
 Cdc1
Battery

S4
S6
Cf2
Fundamental control/PWM control
due to different operation modes
C=450mF
S7
S9
Local
critical
loads
Energy  Cdc2
storage
element 
S8
System Parameter:
Fundamental
frequency :60Hz
Switching frequency:9.6kHz
Rated real power:20kW
iLD 
vLD

S10

vR Receiving-end
Utility

ZR
PWM control
ZR=1Ohm +j12mH
Available operation modes
ZS
Sending-end
Utility
vS
vR Receiving-end
Utility
Local
critical
loads
Equivalent
current source
ZS
Lf1
Cf1
vLD
Local
critical
loads
vR
Local
critical
loads
Receiving-end
Utility
(b) Parallel voltage source operation in stand-alone mode
ZR
Cf2
Cf2
v2
Lf2
Equivalent
voltage source
vS
Sending-end
Utility
v1
vLD
Equivalent
voltage source
(a) Parallel current source operation in grid-connected mode
Progress
ZR
v1
Lf1
ZS
vR
v1
ZR
vLD
vS
Local
critical
loads
Cf1
Receiving-end
Utility
(c) Series voltage source operation in grid-connected mode
Sending-end
Utility
(f) Hybrid Series voltage (back) and parallel current
source (front) operation in grid-connected mode
Equivalent voltage
and current source
vR
Receiving-end
Utility
(d) Hybrid Series voltage (front) and parallel current
source (back) operation in grid-connected mode
ZS
v1
Lf2
ZR
vLD
vS
Cf2
Sending-end
Utility
Reconfigurable power quality regulation system can operate in five
different operation modes to achieve different functions
The converter with energy storage provides reactive power and
harmonic compensation to improve power quality, as well power flow
control between different power grid nodes
Real and reactive power distribution between DC source and energy
storage element
Reduce converter switching loss and increase output voltage boost ratio
High power density and high efficiency
120V(RMS)
Lf2
ZR
vLD
Project Objective
120V(RMS)
Lf2=2.4mH
Cf2=2.5uF
Lf2
200V
Udc2
ONR/ESRDC
Sending-end
Utility
Lf1=2.4mH
Cf1=2.5uF
STS
S2

vS

Cf1
S5
Funding Source
Zs=1Ohm +j12mH
Equivalent voltage
and current source
Local
critical
loads
vR
Receiving-end
Utility
Propose a reconfigurable system topology, Derive five operation
modes and Design system parameters
Analyze operation principle of each mode and develop corresponding
switching modulation schemes for each mode.
Achieve the STATCOM function
Naval Significance
To meet the requirement of pulse load due to the energy storage system
(peak power) in electric ship.
To stabilize the critical load voltage in electric ship
To improve the power quality of electric ship system
To achieve the power flow control between different transmission lines
in electric ship system
2009 ESRDC Team Meeting, 26-27 May, MSU
Algorithm development for evaluating IPS
survivability due to its topology
S. V. Poroseva (CAPS), N. Lay (grad, SC), M. Y. Hussaini (PCSE)
Developed a time–efficient computational graph-based algorithm for
evaluating IPS survivability due to its topology under multiple
simultaneous unrecoverable faults to compare different IPS topologies
and design strategies.
For a given number of faults, the algorithm generates combinations of
faulty elements either deterministically or using Monte Carlo technique
depending on the required accuracy of computations. Then, each
combination is analyzed to determine how much power is available to
loads after the faults. The algorithm supports parallel execution
through OpenMP.
Survivability analysis of a topology of 698 nodes with the total number
of fault combinations ~2698 and the required accuracy of computations
0.5E-3 takes about 2 hours.
2009 ESRDC Team Meeting, 26-27 May, MSU
6
Algorithm development for automated widearea fault detection and location
D. Düştegör (CAPS), S. V. Poroseva (CAPS), M. Y. Hussaini (PCSE)
Objective To develop a new automated wide-area model-based Fault
Detection & Location (FDL) method.
Methodology
Model-Based Fault Diagnosis
Done
input
process
Start
output
Structure Matrix
Yes
Matrix decmp. S+ S0 S-
No
Faults
Detectable
Yes
model
-
residual
residual generation
S+ is empty
residual
processing
decision
logic
residual evaluation
fault
Add one sensor
No
Analysis:
Generate matching
Derive residual structure table
Fault signature table
Current status
Developed a graph-based algorithm
Developed structural models for simple topologies
Analyzed the FDL possibility in these topologies
2009 ESRDC Team Meeting, 26-27 May, MSU
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Other Projects & Collaborations
Related to ESRDC goals
1. Uncertainty Quantification in Power System Simulations
with J. Langston (CAPS, FSU)
2. Application of Network Analysis to Evaluate Grid Vulnerability
with A. Williamson (undergrad, Physics, FSU), Prof. P. Rikvold (Physics, FSU)
3. Integration of Communication and Power Systems
with R. Ford (undergrad, Electrical & Computer Engineering, FSU)
4. Algorithm Development for Smoothing High-Level Noisy Sparse Data
with C. Acosta (grad student, Mathematics, FSU), Prof. M. Y. Hussaini (Program
in Computational Science & Engineering, FSU)
5. Combined Reliability & Topological Survivability Grid Analysis
with Prof. G. Heydt (ASU)
2009 ESRDC Team Meeting, 26-27 May, MSU
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ALL-ELECTRIC SHIP
NOTIONAL THERMAL LOAD DATA
Notional Thermal Data Compiled in collaboration with Research Objectives:
SYNTEK (Rev. 5)
• Win the “battle for data”. Realistic, notional thermal data
is essential to the ESRDC thermal efforts.
Relational database for Notional Thermal Load data
(Rev.1)
Research Accomplishments:
• Notional Thermal Data, including ship location, heat
dissipation under different operation modes, and for
different ambient conditions (10oF and 90oF) have been
compiled. Revision 5 is now available to the ESRDC
team. Missing equipment location and data on power
generation is currently being added. The data is currently
available in excel. For coordination purposes, revisions
are being handled by FSU and Syntek. Updates will be
posted at the ESRDC website.
• A relational database has been created. It allows the user
to perform a search: by zone, by equipment, by heat
dissipation, by location.
Deliverables and Products
• Notional thermal datasheet (Revision 5)
• Relational Database with search capabilities
(Revision 1)
• Both available to ESRDC community at ESRDC
website.
2009 ESRDC Team Meeting, 26-27 May, MSU
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ESRDC Design Tool - Relational Database
Load
visualization
Source: FSU
Temperature
field
calculation
Co-simulations
Relational
Database
(Equipments,
Loads, locations,
operating
conditions,
cooling modes
Source: USC
Ship cooling
system design
Source: FSU
Source: USC
Source: FSU
2009 ESRDC Team Meeting, 26-27 May, MSU
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ALL-ELECTRIC SHIP
HEAT LOAD VISUALIZATION AND TEMPERATURE FIELD
COMPUTATION
Three Dimensional Visualization of Notional Thermal
Data
Research Objectives:
• Determine temperature and humidity inside ship
compartments
• Establish communication with RTDS, VTB and DMTS
for co-simulations
• Develop a tool to evaluate ship level TM strategies.
• Improve the convection heat transfer schemes to better
resolve water/ship interactions
Sample 3D Computation of Temperature Field
Research Accomplishments:
• Grid Generation to match notional data locations has been
automated.
• Industry standard visualization tool (VIsit) from LLNL
can be integrated with any CAD design tool
• Volume Element Method Tool to solve for the associated
ship environment temperature field has been developed
(Revision 3).
Deliverables and Products
• Volume Element Method Based Computational Tool for
Ship Temperature Field Calculation (Revision 3)
• Automated 3D visualization of thermal data (pre and post
TM implementations)
2009 ESRDC Team Meeting, 26-27 May, MSU
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Geographically Distributed Thermo-Electric CoSimulation of All-Electric Ship
Objectives:
Ethernet Switch
OPAL-RT Simulator
Internet
(WAN)
NIC1
Gigabit
Target 2
Target 1
To RTDS Simulator
NIC2
HP
Sonic
Target 3
•
Gateway Server
Router
Switch
Firewall
Target 4
•
•
Advances / Progress / Discoveries:
Host 1
Simulation hardware setup at RTX-Lab, Edmonton
•
•
Setup at CAPS-FSU
Architectural concept of geographically distributed co-simulation
Knot
30
Ship speed
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•
26
24
0
50
100
150
200
250
300
Time (s)
2000
50
1000
0
Controlled temperature of heat sink 1
0
50
3000
200
250
40
300
60
2000
50
1000
0
Uncontrolled temperature of heat sink 2
0
50
100
150
200
250
40
300
200
250
300
Time (s)
200
kW
150
Time (s)
PMD2-Loss
4000
kW-loss
100
•
Temperature
60
PMD1-Loss
Temperature
kW-loss
4000
3000
•
•
100
Pump-power for heat-sink 1
0
50
100
150
Time (s)
Co-simulation results
Modeled thermal and electrical systems
Established Internet based data communication
link between two geographically apart simulators
Investigated the latency of geographically
distributed co-simulation
Stable co-simulation results observed in open loop
and closed loop situations
Naval Significance:
150
50
Monitoring thermo-electric interactions through
HIL simulation
Utilizing geographically available simulation
resources
Perform remotely controlled simulation
•
Understanding of thermo-electric interactions in
electric ships
Design of thermal management system without
any overcompensation
Remote control of simulation and other hardware
2009 ESRDC Team Meeting, 26-27 May, MSU
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Research Efforts in Controls
David Cartes
Sanjeev Srivastava
Wenxin Liu
Karl Schoder
Toria El Mezyani, Siyu Leng, Il-Yop Chung, Shailabh Mazari
2009 ESRDC Team Meeting, 26-27 May, MSU
Projects
1.
Agent Based Reconfiguration in Heterogeneous Environment
Sanjeev Srivastava, Karl Schoder, David Cartes
2.
Reconfigurable Active Front-end of Adjustable Speed Drives for Power Quality
Improvement
Siyu Leng, Wenxin Liu, Il-yop Chung, David Cartes
3.
Intelligent Prognostic Tools for Condition Based Maintenance of Electrical
Machines
Shailabh Mazari, Chris Edrington, Sanjeev Srivastava
4.
Controller Design and Optimization for Bi-directional dc/dc Converter
Il-yop Chung, Karl Schoder
2009 ESRDC Team Meeting, 26-27 May, MSU
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Project 1: Agent Based Reconfiguration in
Environment
Heterogeneous
2009 ESRDC Team Meeting, 26-27 May, MSU
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Agent Based Reconfiguration in Heterogeneous
Environment
Objectives:
•
•
Heterogeneous System
FPGA Interface
Approach:
•
•
Serial Ports
•
•
Advances / Progress / Discoveries:
•
•
Overall heterogeneous system implemented
in MATLAB
Implementation and testing of
reconfiguration algorithm using agents
Develop multi-objective agent system for navy
ship system
Extension of market-based-reasoning approach
for reconfiguration in heterogeneous
environment
Agents implemented in Java & MATLAB
Combination of electrical, chill water, and
thermal system modeled as heterogeneous
system in MATLAB
Agents detect fault in electrical and fluid system
Market-based-reasoning approach for
reconfiguration
Naval Significance:
•
•
•
Load-centric approach for reconfiguration
Optimal autonomous operation; day-today cost savings
Reduced response time, improved
survivability & recoverability, and reduced
manning
2009 ESRDC Team Meeting, 26-27 May, MSU
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Project 2: Reconfigurable Active Front-end of Adjustable Speed Drives for
Power Quality Improvement
2009 ESRDC Team Meeting, 26-27 May, MSU
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Reconfigurable Active Front-end of Adjustable Speed Drives
for Power Quality Improvement
Three-Phase
Power Grid
Diode Rectifier
Objectives:
R_load L_load
•
R
Point of
Common
Coupling
L
I_source
I_load
•
IGBT Inverter
IGBT Rectifier
R_filter L_filter
PMSM
C
•
I_filter
Back Stage
Machine Drive
Control Block
Active Front-end
Control Block
Advanced
Harmonic
Cancellation
Module
Motor
Control
Module
Approach:
•
•
Advances / Progress / Discoveries:
•
•
Improved the previous adaptive MAFC algorithm
and implemented in closed loop
Designed and implemented a Real Time Particle
Swarm Optimization (RT-PSO) based harmonic
identification algorithm
Design advanced algorithms for current
harmonic detection
Use the identified harmonic information to
generate reference signals for harmonic
cancellation
Use the active front end to realized multiple
functions
Designed a Lyapunov based adaptive algorithm
to selectively identify harmonic contents of
interest
Designed a RT-PSO based algorithm to identify
fundamental signals directly from contaminated
current signals
Naval Significance:
•
•
Improved power quality and power factor
Implemented multiple functions (current
harmonics cancellation, reactive power
compensation, and regulated DC output voltage)
with the one active front end of Motor Drive
2009 ESRDC Team Meeting, 26-27 May, MSU
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Project 3: Intelligent Prognostic Tools for Condition Based Maintenance of
Electrical Machines
2009 ESRDC Team Meeting, 26-27 May, MSU
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Intelligent Prognostic Tools for Condition Based Maintenance
of Electrical Machines
Objective:
•
Drive System
PMAC Experimental Test Bed
Approach:
•
•
•
d-SPACE Interface Rack
Progress:
•
Developing hi-fidelity PMAC machine models
using Finite Element Analysis (FEA)
Implementing the RT-PSO based parameter
identification algorithm using d-SPACE®
hardware controller
Carrying out fault diagnosis tests using the
drive system
Naval Significance:
•
A generic model for PMAC machine (control based)
in Simulink® is being designed
Design and develop intelligent prognostic tools
for fault diagnosis and support for Condition
Based Maintenance (CBM) of Shipboard
Power Systems (SPS)
•
CBM can monitor the exact condition of
individual components
Makes maintenance proactive by spotting fault
sources well before any failure occurs in the
Shipboard Power Systems (SPS)
2009 ESRDC Team Meeting, 26-27 May, MSU
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Project 4: Controller Design and Optimization
for Bi-directional dc/dc Converter
2009 ESRDC Team Meeting, 26-27 May, MSU
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Controller Design and Optimization
for Bi-directional dc/dc Converter
Aux.
Gen
Gen
AC/DC
AC/DC
Pulsed
Load
Objectives:
Distributed Sources
Critical Loads
HP
Sensors
Energy
Storage
Flywheel/
High Speed
Genset
DC/AC
MVDC Ring Bus (5kVdc)
Aux.
Gen
Propulsion
Motors
AC/DC
DC/AC
4 MW
Gen
Bi-directional
DC/DC
Converter
AC/DC
36.5 MW
Generators
Prop.
Mot.
•
Prop.
Mot.
Other Zonal
Load Centers
(2 – 5)
Bi-directional
DC/DC
Converter
•
800Vdc
Approach:
•
Energy
Storage/
Source
Energy
Storage/
Source
•
Zonal Load
Center 1
Ship Service
Power
•
Advances / Progress / Discoveries:
•
•
Bi-directional power control for both buck
and boost modes
Integration of bi-directional converter model
with large-scale real-time shipboard power
systems
Develop large-signal model and small-signal
model of multiple control units
Develop control parameter optimization
schemes considering various operating
conditions
Using switching average model for large and
small signal model development
Particle swarm optimization for control
parameter tuning
Frequency domain analysis such as eigenvalue
study and stability margin analysis
Naval Significance:
•
•
•
Energy efficiency improvement of
shipboard power system
Coordination of bi-directional converters
and other generators
Stable steady-state control performance
in each mode and between modes
2009 ESRDC Team Meeting, 26-27 May, MSU
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Bi-directional DC/DC converter
• Circuit diagram of bi-directional DC-DC Converter
2009 ESRDC Team Meeting, 26-27 May, MSU
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Notional MVDC System
Development on RTDS
Model Updates:
•
PCM-1/1A now isolated and bidirectional
•
Load center model expanded to include
450VAC & DC constant power, constant
impedance and pump/fan motor loads
AC/DC Converter
Main AC
Generator 1

Energy Storage
MTG1
=
Auxilary AC
Generator 1
GT
GT
DC/DC
Converter
=

=

Capacitor
Bank
Drive Inverter
Demonstrated the viable use of PCM-4
local voltage droop control as a backup
to centralized power management
system control for maintaining MVDC
bus stability
•
=
AC Circuit
Breaker
DC
Disconnect
=
•
AC/DC Converter
ATG1
AC Circuit
Breaker
Model Application: Study of MVDC
Bus Stability
Paper presented at ASNE APS 08
MTG1 & MTG2 Output Currents
DC
Disconnect
Port
Propulsion
Motor
ATG1 & ATG2 Output Currents
Droop Control After Loss of Central Control
MVDC
Port BusMTG1 & MTG2 Output Currents
ATG1 & ATG2 Output Currents
All Generator
pu Output
Powers
=
=
DC/DC
Converter
PMS
MTG1 & MTG2 Output Voltages
Stern
Cross-hull
Disconnect
Radar
See
separate
figure for
details
Zone 4
Load
Center
Zone 3
Load
Center
Zone 2
Load
Center
Bow
Cross-hull
Disconnect
Zone 1
Load
Center
ATG1 & ATG2 Output Frequencies
All Generator
pu Output
Powers
=
Request
power fr
load shar
routin
=
Zone 5
Deck house
MTG1PR
MTG1 & MTG2 Output Voltages
∑
MTG1 & MTG2 Output
Frequencies
Pulsed
MVDC
Starboard Bus
-
Load
=


Drive Inverter
AC Circuit
Breaker
=
AC/DC Converter
ATG2
Auxilary AC
Generator 2
GT
GT
Starboard
Propulsion
Motor
AC Circuit
Breaker
MTG2
Main AC
Generator 2
ATG1 & ATG2 Output Frequencies
MTG1 & MTG2
Output
Powers
=
=
DC/DC
Converter

=
Pulse
Charging
Circuit
MTG1 & MTG2
Output
Powers
Load po
deman
MTG1P
MTG1 & MTG2 Output Frequencies
AC/DC Converter
MTG1 & MTG2
Output
Powers
2009 ESRDC Team Meeting, 26-27 May, MSU
MTG1 & MTG2
Output
Powers
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P
s
PEBB-based MVDC PHIL Setup
Hardware
Represents a
PCM-1
Converter
HUT
4.16 kV / 7 MVA
utility bus
CAPS
Facility
Testbed
Software
600 VDC
bus voltage
DC/DC
converter
VVS 2
DC
Contactor
RTDS
Controlled
600 VDC
rail-to-rail
.
Zonal
resistive
DC load step
circuit
0….4.16 (8.2) kV / 6.25 MVA
experimental AC bus (ungrounded)
480 VAC
RTDS
Controlled
.
Energy Flow
0-480 V / 1.5 MVA
AC bus (ungrounded)
•
•
•
DC
Contactor/solid
state breaker
Representative
fault resistance
AC/DC
converter
Bolted fault switch
•
Zonal
DC fault
circuit
RTDS
Controlled
AMSC PEBB
modules and FP
controller board
HUT
Software
Approach:
3. Uncontrolled induction
motor load
800 VDC
rail-to-rail
Resistor
load bank
system performance
studies using lowvoltage, PEBB-based
PHIL simulation
2. Resistive load
Total Load
Current
Demand
VVS 1
Modulator
reference voltages
• Goal: Conduct MVDC
1. Constant power load
AMSC PEBB
modules and FP
controller board
5 MW Variable
Voltage Source
Converters
RTDS E-ship Model
PCM-2 Load
Models
Main Gasturbine
Generator
modeled in
RTDS E-ship
Model
Represents a
PCM-4
Rectifier
3 Ø Current
Feedback
Configure PEBB modules and MSU-USC controls into AC/DC and
DC/DC converters with CAPS’ Variable Voltage Source (VVS) testbed
and the RTDS E-ship model to emulate shipboard PCM-1 and PCM-4
converters
Create a “software-only” model of the entire PHIL setup on RTDS for
“de-risking” test planning
Conduct PHIL experiments
2009 ESRDC Team Meeting, 26-27 May, MSU
ESRDC collaboration:
•
•
•
•
•
•
Hardware test facility
– FSU/CAPS
PEBB modules from
MSU
AC/DC converter
controls – MSU
DC/DC converter
controls – USC
VTB load center
model – RWTH
RTDS MVDC E-ship
Model – FSU
30
Investigating Shipboard Electric
Grounding Issues
Objectives:
•
•
Explore the various issues surrounding
the selection and application of
grounding on the ship
Identify areas of power system studies,
i.e. operation and protection, impacted by
grounding selection
Approach:
•
•
Advances / Progress / Discoveries:
•
•
•
Convert a ship section into a mesh
Inject currents into the nodes of the mesh
and obtain an equivalent circuit for the ship
section
Grounding options under consideration:
high and low impedance grounding
Model ship section in Maxwell 3D and
identify areas where stray currents are
most likely to flow due to ship’s geometry
Study and compare the advantages and
disadvantages of grounding choices in
other ships
Naval Significance:
•
•
•
Safety and reliability
Management of ground fault currents and
stray currents
Cathodic corrosion prevention
2009 ESRDC Team Meeting, 26-27 May, MSU
32
Development of a Virtual Machine (VM) for
Advanced Motor Drive Evaluations
VSD
AMP
Objectives:
•
SENSOR
simulated
•
Naval Significance:
•
•
•
De-risk model validation of prototype
machines, new drive system topologies,
and/or advanced control system strategies
Test Variable speed drives (VSD) with
different types of machines
CAPS to extend the Virtual Machine concept
into MW power range
•
Approach:
•
•
Advances / Progress / Discoveries:
•
•
•
Amplifier/transformer voltage phase
synchronization
High frequency noise removed via sine filter at
output of VSD inverter
Currently working on PHIL time step
synchronization and IM model in RTDS
Utilize Power-Hardware-in-the-loop
(PHIL) to model a real world machine
(motor with mechanical load) in real
time digital simulator (RTDS)
VM’s electrical characteristics from
torque/speed behavior represent the
target machine
Remove the need for need for a real
rotating machine
•
•
Test concept via developing a 25 kW
PHIL test bed
Model an induction machine (IM) within
DURIP setup
25 kVA voltage amplifier interfaces
simulated VM with VSD under test
Danfoss AC drive references VM and
supplies amplifier current through
transformer coupled LC filter
2009 ESRDC Team Meeting, 26-27 May, MSU
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Unique high speed machinery testing
facility at CAPS
• Gaer box from
DURIP grant
• Team
– FSU (Steurer)
– NSWCCD (Kolesar)
• Applications
– Testing medium and
high-rpm machinery
• Uniqueness at CAPS
– Dynamic torque from
real time models of
mechanical prime
movers or loads
– Dynamic
voltage/current from
real time models of
electrical source or
load
Real time simulator RTDS
Variable Voltage Source
(VVS) Converter
40-400 Hz
0…4.16 kV
5 MW
24 krpm
0-60 Hz
0…3 kV
2 x 2.5MW
450 rpm
2
1
3600 rpm
2009 ESRDC Team Meeting, 26-27 May, MSU
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High Speed Gear Box
•
•
•
•
•
Material cost from ONR DURIP grant N00014-08-1-0805
Order Awarded to LUFKIN
Delivery April 2010
Installation and Commissioning May 2010
Engineering drawings June 2009
2009 ESRDC Team Meeting, 26-27 May, MSU
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High Speed Gear Box
• Ratings
•
•
•
•
•
Power rating:
Overload:
Torque overload:
Speed Stage 1:
Speed Stage 2:
5,000 kW
10,000 kW for 1 minute
300% around zero speed
1800/3600 RPM
12,000/24,000 RPM
2009 ESRDC Team Meeting, 26-27 May, MSU
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High Speed Dynamometer
2009 ESRDC Team Meeting, 26-27 May, MSU
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