SlideShare a Scribd company logo
1 of 37
PERFORMANCE ANALYSIS OF
A NETWORK BASED, ULTRAFAST
CENTRALIZED FAULT IDENTIFICATION AND
LOCATION SYSTEM
Advisor: Dr. Ming Yu
Co-advisor: Dr. Michael Steurer
Committee member: Dr. Hui Li
7/12/2016 1
Presenter: Shravan Tamaskar
M.S. Thesis Defense: 6 June 2016
Outline
 Overview
– Motivation
– Objective and key contribution
 Introduction to Centralized Fault identification and Location (CFL) system
architecture
 Performance modeling of CFL system
 Analyzing the factors affecting the CFL system performance
 Validation: CFL demonstration and implementation
 Conclusion and Future work
7/12/2016 2
Motivation: CFL
 Fault management in
medium voltage direct
current (MVDC)
shipboard power system
(SPS) aimed to be
accomplished in 8 ms
7/12/2016 3
 A need for
fast fault
identification
system
necessary
 This led to the
development of
centralized fault
identification and
location (CFL)
system
8 ms
Objective
■ To develop a testbed for
an ultrafast fault
identification system for
the MVDC SPS
■ To model, analyze and
validate the performance
of the CFL system
■ To analyze the scaling
and the factors affecting
the CFL system
performance
Key Contribution
■ Modeling of
– EtherCAT Frame
– CFL decision time
■ Scaling of CFL system based on
– Frame
– Cycle time
■ Performance parameters
– Topology
– Preliminary noise analysis
■ Developed a CFL testbed and
implemented using different
system configurations
7/12/2016 4
7/12/2016 5
Fault Management in MVDC SPS
Fault Management in MVDC SPS
Rapid fault identification
Fault
Identification
Fault Clearing
highly-coordinated interaction
Detect and
localize fault
Re-energize
system
De-energize
system
Isolate
faulted
segment
Detect &
locate
8 ms
Introduction to CFL architecture
■ CFL architecture
■ Differential protection scheme
■ CFL process description
7/12/2016 6
CFL architecture
7/12/2016 CAPS, FSU 7
CS- Cable Section
PGM- Power Generation Module
Disconnect Switch
CS1 CS2 CS3
CS4
CS5CS6CS7
CS8
PG
M
PG
M
Load
Load
CFL
Power System
No Fault
Differential protection scheme
7/12/2016 CAPS, FSU 8
Operates based on
Percentage Differential Protection (PDP) scheme
CS- Cable Section DS- Disconnect Switch
LIF test case
Slope diagram of protection scheme
DSA
DSA DS B
DS BCS
CS
Normal
Operation
During Fault
A
B
Time
msΔI
+Ia
-Ib
| 𝑛=2
𝑛
𝐼 𝑛| − 𝑆 . 𝑛=2
𝑛
|𝐼 𝑛| ≥ 𝐼𝑚𝑖𝑛
7/12/2016 CAPS, FSU 9
 Main parts of CFL system
 A master unit with fault protection algorithm
 Several slave units that perform data acquisition and send digitized
current data to master unit for decision making
 A communication (EtherCAT) protocol governing master- slave
topology
Master
(Algorithm)
Line topology
Slave nSlave 1 Slave 2
Generic CFL system Architecture
EtherCAT Hardware CAPS Capability In-use
Master 1 1
I/O nodes 20 9
Slaves 6 6
7/12/2016 10
Master
Condition
check
Counter
Increment
Counter
threshold
Trip
True
slave1slave n
False
EtherCAT Frame
YesNo
CFL process description
Data signal
Logic signal
Reset
counter
 Frame modeling
 Cycle time modeling
 Decision time
1. RTDS processing
2. Hardware sync
3. Beckhoff processing
7/12/2016 11
Performance Modeling
7/12/2016 12
EtherCAT Frame
Frame Modeling
7/12/2016 13
𝐷𝐺 𝑝𝑙 = (𝑛 𝐹𝑂 x 𝐿 𝐹𝑂 + 𝑛 𝐴𝐼 x 𝐿 𝐴𝐼 + 𝑛 𝐷𝑂 x 𝐿 𝐷𝑂 )
𝐿 𝐷𝐺 = 𝐷𝐺=1
𝐷𝐺
(𝐷𝐺 𝐻 + 𝐷𝐺 𝑝𝑙 + 𝐷𝐺 𝑤𝑘𝑐 )
𝐿 𝐹𝑟𝑎𝑚𝑒 = 𝐸 𝑇𝑦𝑝𝑒 + 𝐿 𝑐𝑚𝑑 + 𝐸𝑐𝑎𝑡 𝐻 + 𝐿 𝐷𝐺
Description Abbreviation Size (Byte)
EtherType 𝐸 𝑇𝑦𝑝𝑒 2
Commands 𝐿 𝑐𝑚𝑑 10
EtherCAT Header 𝐸𝑐𝑎𝑡 𝐻 2
Datagram Header 𝐷𝐺 𝐻 10
No. of Slaves 𝑛 𝑠𝑙𝑎𝑣𝑒𝑠 6
No. of Analog Input
channel
𝑛 𝐴𝐼
No. of Digital Output
channel
𝑛 𝐷𝑂
No. of Fiber Optic
connecter
𝑛 𝐹𝑂
Size of Analog Input 𝐿 𝐴𝐼 4
Size of Digital Output 𝐿 𝐷𝑂 3
Size of Fiber Optic
connecter
𝐿 𝐹𝑂 2
Datagram working
counter
𝐷𝐺 𝑤𝑘𝑐 2
Simulated number of frames
7/12/2016 14
𝑇𝑓𝑟𝑎𝑚𝑒 =
𝐿 𝑓𝑟𝑎𝑚𝑒 × 8
𝑏𝑤
Frame transmission time
nFrame = ceiling (
𝐿𝑒𝑛𝑔𝑡ℎ 𝑜𝑓 𝐹𝑟𝑎𝑚𝑒
1500
)
Time taken by the controller
to transmit the bits in the
frame
Cycle Time
7/12/2016 15
𝑇𝑐 = 2 × (( 𝑁 𝑇 + 1) × 𝑇𝑝+ 𝑇 𝑀
𝑓
+ (𝑁 𝑇 × 𝑇𝑆
𝑓
) + 𝑇𝑐
𝑝
)
Master
Slave
1
Slave
2
Slave
n
Defined as the time
necessary for the
exchange of input/output
data between the
controller and all
networked devices once
Simulated cycle time
Measured cycle timeMeasured cycle time
20.22 µs
16.73 µs
Number of slaves
Minimumcycletime(µs)
20.96 µs
Communication
System
Power System
CFL Testbed
7/12/2016 CAPS, FSU 16
RTDS
SPS
Simulation
Slaves
AI, DO
Master
(Protection
algorithm)
Analog
Signals
Digital
Signals
Simulates
Fault
Initiates fault
clearing sequence
EtherCAT Packet
Simulation timestep- 50 µs
Cycle
Time
50 µs
M ss s
CS4
CS8
PGM Load
PGM Load
CFL decision time-
RTDS processing
7/12/2016 17
tRTDS = nproc step x tSimulationTimeStep
Time taken by RTDS (tRTDS) to process the
simulation logic and generate a signal which
goes out of RTDS analog output
Decision time
• RTDS
processing
• Beckhoff
processing
• Synchronization
mismatch
CFL Decision Time-
Beckhoff Processing
7/12/2016 18
The time taken by the beckhoff (tbeckhoff)
system to read the signals and compute the
algorithm and generate a response signal.
Cycle time (tct) 50 µsCycle time (tct) 100 µs
tbeckhoff = (niter + 1) x tct
600 µs
5 iterations (niter) for fault
identification,
(n+1) 6 timesteps
fault initiation signal
fault detection by CFL
300 µs
Yellow
-
Blue-
CFL Decision Time-
Synchronization mismatch
7/12/2016
19
Additional time added to the system operation due to simulation
delays and delays in the logic processing and hardware interfacing
tmismatch = thsm+ tbpd
RTDS
SPS
Simulation
Slaves
AI, DOAnalog
Signals
No sync
Beckhoff
processing
delay
(tbpd)
Hardware
Synchronization
Mismatch
(thsm)
Worst timing
2 cycle time
1 cycle
time Best
timing
CFL Decision Time
7/12/2016 20
Decision time is the sum of all the individual timings to detect a fault in the SPS
td = tRTDS + tbeckhoff + tmismatch
Fault initialization
RTDS output to slaves
CFL decision out
RTDS trip signal
Time (µs)
CFL Decision Time
7/12/2016 21
0 100 200 300 400 500 600 700 800 900
Total
RTDS Processing
RTDS Processing
Hardware Sync
Beckhoff error
Cycle 1
Cycle 2
Cycle 3
Cycle 4
Cycle 5
(n+1)th cycle
RTDS Processing
time (µs)
CFL Timing Analysis- Individual Split-up
Hardware sync
Beckhoff delay
1. Topology
– Line
– Ring
2. Jitter
3. Bandwidth
4. Network propagation time
5. Noise
– AWGN / SNR
– Noise on CFL System
7/12/2016 22
Performance parameters
Performance parameters- Topology
7/12/2016 23
Master Slave 1 Slave 2 Slave n
Ring topology
Additional/ return path
Master Slave 1 Slave 2 Slave n
Line topology
Return path
Tcycle = Tframe + Tnetwork
Advantages of Ring
topology
1. Resilient to 1
cable cut
condition
2. Additional path
for packet flow
3. Better cycle time
for large
systems
Theoretical minimum cycle time
Performance parameters- Jitter
7/12/2016 24
J = |Tc − Tcm|
TC - set cycle time
(eg. 50 µs)
Tcm - measured cycle time
Causes-
• Network
congestion
• Improper queuing
• Configuration
errors
Jitter can be described as latencies in the network
components which may result in the variation of the cycle
time
Jitter (simulated) per slave during the execution of the CFL
system configured at 50 µs
Performance parameters-
Bandwidth
7/12/2016 25
NRB =
|Tc − MCT|
Tc
× 100
MCT- Minimum cycle time
TC – set cycle time value
NRB- Non-realtime bandwidth
Line
Topology
Theoretical extrapolation showing the comparison of Fast Ethernet and gigabit Ethernet
The affect of bandwidth on
cycle time with respect to
slaves
Number of slaves
Minimumcycletime(µs)
Line
Topology
Number of slaves
Minimumcycletime(µs)
Fast Ethernet 100 Mbps
Gigabit Ethernet 1 Gbps
Performance parameters-
Network propagation time
7/12/2016 26
• Forwarding delays produced by slave devices
• Cable propagation delays
Theoretical network propagation time
networkpropagationtime(µs)
Number of slaves
Performance parameters-
Noise
7/12/2016 27
Additive White Gaussian noise SNR = 20 × log10(
𝑉 𝑠𝑖𝑔𝑛𝑎𝑙
𝑉 𝑛𝑜𝑖𝑠𝑒
)
Higher the SNR
Lower the noise in the
signal
Better the
measurement reading
Definition:
Noise is a random,
undesirable energy that
enters the
communication system
via the communicating
medium and interferes
with the transmitted
message
Preliminary analysis: Focused on
the effect of noise on the CFL
detection before the fault occurs.
Question:
Can noise create a false
identification?
Noise
Signal
Receiver
Signal +
Noise
Performance parameters-
Noise: CASE 1
7/12/2016 28
CASE 1:
Noise in one measurement node
measurement node
Timestep
Performance parameters-
Noise CASE 2
7/12/2016 29
CASE 2:
Noise in both the measurement nodes
measurement node
Timestep
CFL demonstration and
implementation
Norbert Doerry’s MVDC SPS architecture
7/12/2016 30
SPS model
7/12/2016 31
1 MW PGM is interfaced to 5 kV MVDC bus
CS1 CS2 CS3
CS4
CS5CS6CS7
CS8
F I O
FIO
F
IO
F I O
F
I
O
Master
F
I
O
LOADInput signals (Current) from RTDS to Analog Input
Output signal from Digital Output to RTDS GTDI
Master Slave Connection (Fiber)
Disconnect Switch
CS- Cable Section
I –Analog Input Terminal
O–Digital Output Terminal
F –Fiber optic converter junction
F
I
O
Slave
UnitMMC LOAD
MMC 1
PG
M
PG
M
Load
Load
CFL Demonstration
7/12/2016 CAPS, FSU 32
t0 – RTDS simulation
logic processing
t1 – CFL decision time
t2 – synchronization
mismatch and
simulation logic
processing
CHIL implementation
of CFL system
t0
t1 t2
750 µs
time (ms)
0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85
time (ms)
Fault Simulation
RTDS trip signal
Implementation
Condition Type Time (µs)
Fault impedance Low impedance fault
300
High impedance fault
Power system
configuration
Open ring
Closed ring
Loading condition 0.544 MW
0.125 MW
Operating modes VSM- CSM
VSM- VSM
7/12/2016 33
VSM- Voltage source mode
CSM- Current source mode
■ Models to determine the performance and scaling of CFL
system were developed
■ Analyzed and discussed the factors affecting the CFL
performance
■ The effectiveness of the model has been verified.
■ A CFL, based on percentage differential protection,
demonstrates fault detection time of ~300 µs.
■ The CFL system was tested for various system operating
conditions and the results demonstrate its desired
performance
■ The ultrafast fault identification system paves the way to
accomplish fault management in the desired 8 ms time
frame
7/12/2016 34
Conclusion
■ Hardware Implementation of a ring topology
■ Validating the system resiliency for cable cut condition
■ System level control
■ Exhaustive Noise analysis
■ Integrating multiple CFL units
7/12/2016 35
Future Work
References
1. Shravan Tamaskar, Harsha Ravindra, Mike Sloderbeck, Ruturaj Soman, and Michael Steurer.
"CHIL-based Demonstration of Centralized Fault Location Strategy for a MVDC Shipboard Power
System."
2. Qiu Deng, Xing Liu, Ruturaj Soman, Michael Steurer, and Roger A. Dougal. "Primary and backup
protection for fault current limited MVDC shipboard power systems." In Electric Ship Technologies
Symposium (ESTS), 2015 IEEE, pp. 40-47. IEEE, 2015.
3. Michael J. Thompson, "Percentage restrained differential, percentage of what?." In Protective
Relay Engineers, 2011 64th Annual Conference for, pp. 278-289. IEEE, 2011.
4. https://www.ethercat.org/
5. http://infosys.beckhoff.com/
6. Ziyuan Cai, and Ming Yu. "Modeling and Simulation of a Real-time Ethernet Protocol for Smart
Grids." International Journal Of Intelligent Control And Systems 17, no. 3 (2012): 69-78.
7. Mladen Knezic, Branko Dokic, and Zeljko. Ivanovic. "Topology aspects in EtherCAT networks."
In Proceedings of 14th International Power Electronics and Motion Control Conference EPE-
PEMC 2010. 2010.
8. B. P. Lathi (1968). Communication systems. New York, Wiley.
9. J. A. Betts (1970). Signal processing, modulation and noise. London, English Universities.
7/12/2016 36
7/12/2016 37

More Related Content

What's hot

SREcon 2016 Performance Checklists for SREs
SREcon 2016 Performance Checklists for SREsSREcon 2016 Performance Checklists for SREs
SREcon 2016 Performance Checklists for SREsBrendan Gregg
 
High performance digital predistortion for wideband RF power amplifiers
High performance digital predistortion for wideband RF power amplifiersHigh performance digital predistortion for wideband RF power amplifiers
High performance digital predistortion for wideband RF power amplifiersLei Guan (Phd, SM-IEEE)
 
SAND: A Fault-Tolerant Streaming Architecture for Network Traffic Analytics
SAND: A Fault-Tolerant Streaming Architecture for Network Traffic AnalyticsSAND: A Fault-Tolerant Streaming Architecture for Network Traffic Analytics
SAND: A Fault-Tolerant Streaming Architecture for Network Traffic AnalyticsQin Liu
 
Timing synchronization F Ling_v1
Timing synchronization F Ling_v1Timing synchronization F Ling_v1
Timing synchronization F Ling_v1Fuyun Ling
 
Practical issues to be considered in PHY layer of 802.11 standard spec
Practical issues to be considered in PHY layer of 802.11 standard specPractical issues to be considered in PHY layer of 802.11 standard spec
Practical issues to be considered in PHY layer of 802.11 standard specEalwan Lee
 
Timing closure document
Timing closure documentTiming closure document
Timing closure documentAlan Tran
 
Topograhical synthesis
Topograhical synthesis   Topograhical synthesis
Topograhical synthesis Deiptii Das
 
Clock mesh sizing slides
Clock mesh sizing slidesClock mesh sizing slides
Clock mesh sizing slidesRajesh M
 
Design Of A PI Rate Controller For Mitigating SIP Overload
Design Of A PI Rate Controller For Mitigating SIP OverloadDesign Of A PI Rate Controller For Mitigating SIP Overload
Design Of A PI Rate Controller For Mitigating SIP OverloadYang Hong
 
Implementing Useful Clock Skew Using Skew Groups
Implementing Useful Clock Skew Using Skew GroupsImplementing Useful Clock Skew Using Skew Groups
Implementing Useful Clock Skew Using Skew GroupsM Mei
 
Phase-Locked Loop (PLL) and Carrier Synchronization Fuyun Ling_v1.3
Phase-Locked Loop (PLL) and Carrier Synchronization Fuyun Ling_v1.3Phase-Locked Loop (PLL) and Carrier Synchronization Fuyun Ling_v1.3
Phase-Locked Loop (PLL) and Carrier Synchronization Fuyun Ling_v1.3Fuyun Ling
 
Webinar Slides: Probing Techniques and Tradeoffs – What to Use and Why
Webinar Slides: Probing Techniques and Tradeoffs – What to Use and WhyWebinar Slides: Probing Techniques and Tradeoffs – What to Use and Why
Webinar Slides: Probing Techniques and Tradeoffs – What to Use and Whyteledynelecroy
 
Emerson Eduardo Rodrigues - ENGINEERING STUDIES1 Rp 160534 - clean
Emerson Eduardo Rodrigues - ENGINEERING STUDIES1 Rp 160534 - cleanEmerson Eduardo Rodrigues - ENGINEERING STUDIES1 Rp 160534 - clean
Emerson Eduardo Rodrigues - ENGINEERING STUDIES1 Rp 160534 - cleanEMERSON EDUARDO RODRIGUES
 
YOW2018 Cloud Performance Root Cause Analysis at Netflix
YOW2018 Cloud Performance Root Cause Analysis at NetflixYOW2018 Cloud Performance Root Cause Analysis at Netflix
YOW2018 Cloud Performance Root Cause Analysis at NetflixBrendan Gregg
 
DEEP-mon: Dynamic and Energy Efficient Power monitoring for container-based i...
DEEP-mon: Dynamic and Energy Efficient Power monitoring for container-based i...DEEP-mon: Dynamic and Energy Efficient Power monitoring for container-based i...
DEEP-mon: Dynamic and Energy Efficient Power monitoring for container-based i...NECST Lab @ Politecnico di Milano
 

What's hot (20)

SREcon 2016 Performance Checklists for SREs
SREcon 2016 Performance Checklists for SREsSREcon 2016 Performance Checklists for SREs
SREcon 2016 Performance Checklists for SREs
 
High performance digital predistortion for wideband RF power amplifiers
High performance digital predistortion for wideband RF power amplifiersHigh performance digital predistortion for wideband RF power amplifiers
High performance digital predistortion for wideband RF power amplifiers
 
SAND: A Fault-Tolerant Streaming Architecture for Network Traffic Analytics
SAND: A Fault-Tolerant Streaming Architecture for Network Traffic AnalyticsSAND: A Fault-Tolerant Streaming Architecture for Network Traffic Analytics
SAND: A Fault-Tolerant Streaming Architecture for Network Traffic Analytics
 
Timing synchronization F Ling_v1
Timing synchronization F Ling_v1Timing synchronization F Ling_v1
Timing synchronization F Ling_v1
 
Practical issues to be considered in PHY layer of 802.11 standard spec
Practical issues to be considered in PHY layer of 802.11 standard specPractical issues to be considered in PHY layer of 802.11 standard spec
Practical issues to be considered in PHY layer of 802.11 standard spec
 
Timing closure document
Timing closure documentTiming closure document
Timing closure document
 
Topograhical synthesis
Topograhical synthesis   Topograhical synthesis
Topograhical synthesis
 
Clock mesh sizing slides
Clock mesh sizing slidesClock mesh sizing slides
Clock mesh sizing slides
 
Mmap failure analysis
Mmap failure analysisMmap failure analysis
Mmap failure analysis
 
3 gpp lte-rlc (1)
3 gpp lte-rlc (1)3 gpp lte-rlc (1)
3 gpp lte-rlc (1)
 
Time Synchronisation
Time SynchronisationTime Synchronisation
Time Synchronisation
 
BDL_project_report
BDL_project_reportBDL_project_report
BDL_project_report
 
Design Of A PI Rate Controller For Mitigating SIP Overload
Design Of A PI Rate Controller For Mitigating SIP OverloadDesign Of A PI Rate Controller For Mitigating SIP Overload
Design Of A PI Rate Controller For Mitigating SIP Overload
 
Implementing Useful Clock Skew Using Skew Groups
Implementing Useful Clock Skew Using Skew GroupsImplementing Useful Clock Skew Using Skew Groups
Implementing Useful Clock Skew Using Skew Groups
 
Phase-Locked Loop (PLL) and Carrier Synchronization Fuyun Ling_v1.3
Phase-Locked Loop (PLL) and Carrier Synchronization Fuyun Ling_v1.3Phase-Locked Loop (PLL) and Carrier Synchronization Fuyun Ling_v1.3
Phase-Locked Loop (PLL) and Carrier Synchronization Fuyun Ling_v1.3
 
Precision clock synchronization_wp
Precision clock synchronization_wpPrecision clock synchronization_wp
Precision clock synchronization_wp
 
Webinar Slides: Probing Techniques and Tradeoffs – What to Use and Why
Webinar Slides: Probing Techniques and Tradeoffs – What to Use and WhyWebinar Slides: Probing Techniques and Tradeoffs – What to Use and Why
Webinar Slides: Probing Techniques and Tradeoffs – What to Use and Why
 
Emerson Eduardo Rodrigues - ENGINEERING STUDIES1 Rp 160534 - clean
Emerson Eduardo Rodrigues - ENGINEERING STUDIES1 Rp 160534 - cleanEmerson Eduardo Rodrigues - ENGINEERING STUDIES1 Rp 160534 - clean
Emerson Eduardo Rodrigues - ENGINEERING STUDIES1 Rp 160534 - clean
 
YOW2018 Cloud Performance Root Cause Analysis at Netflix
YOW2018 Cloud Performance Root Cause Analysis at NetflixYOW2018 Cloud Performance Root Cause Analysis at Netflix
YOW2018 Cloud Performance Root Cause Analysis at Netflix
 
DEEP-mon: Dynamic and Energy Efficient Power monitoring for container-based i...
DEEP-mon: Dynamic and Energy Efficient Power monitoring for container-based i...DEEP-mon: Dynamic and Energy Efficient Power monitoring for container-based i...
DEEP-mon: Dynamic and Energy Efficient Power monitoring for container-based i...
 

Similar to Thesis

Amplification, ROADM and Optical Networking activities at CPqD
Amplification, ROADM and Optical Networking activities at CPqDAmplification, ROADM and Optical Networking activities at CPqD
Amplification, ROADM and Optical Networking activities at CPqDCPqD
 
Configuring the communication on FlexRay: the case of the static segment
Configuring the communication on FlexRay: the case of the static segmentConfiguring the communication on FlexRay: the case of the static segment
Configuring the communication on FlexRay: the case of the static segmentNicolas Navet
 
Klessydra t - designing vector coprocessors for multi-threaded edge-computing...
Klessydra t - designing vector coprocessors for multi-threaded edge-computing...Klessydra t - designing vector coprocessors for multi-threaded edge-computing...
Klessydra t - designing vector coprocessors for multi-threaded edge-computing...RISC-V International
 
Provisioning Bandwidth & Logical Circuits Using Telecom-Based GIS .
Provisioning Bandwidth & Logical Circuits Using Telecom-Based GIS.Provisioning Bandwidth & Logical Circuits Using Telecom-Based GIS.
Provisioning Bandwidth & Logical Circuits Using Telecom-Based GIS .SSP Innovations
 
CRC AND TRANSMIT ERROR REPORT
CRC AND TRANSMIT ERROR REPORTCRC AND TRANSMIT ERROR REPORT
CRC AND TRANSMIT ERROR REPORTAlex TX
 
Barcelona Supercomputing Center, Generador de Riqueza
Barcelona Supercomputing Center, Generador de RiquezaBarcelona Supercomputing Center, Generador de Riqueza
Barcelona Supercomputing Center, Generador de RiquezaFacultad de Informática UCM
 
Globecom 2015: Adaptive Raptor Carousel for 802.11
Globecom 2015: Adaptive Raptor Carousel for 802.11Globecom 2015: Adaptive Raptor Carousel for 802.11
Globecom 2015: Adaptive Raptor Carousel for 802.11Andrew Nix
 
BFSK RT In FPGA Thesis Pres Jps
BFSK RT In FPGA Thesis Pres JpsBFSK RT In FPGA Thesis Pres Jps
BFSK RT In FPGA Thesis Pres Jpsjpsvenn
 
ROLE OF DIGITAL SIMULATION IN CONFIGURING NETWORK PARAMETERS
ROLE OF DIGITAL SIMULATION IN CONFIGURING NETWORK PARAMETERSROLE OF DIGITAL SIMULATION IN CONFIGURING NETWORK PARAMETERS
ROLE OF DIGITAL SIMULATION IN CONFIGURING NETWORK PARAMETERSDeepak Shankar
 
Achitecture Aware Algorithms and Software for Peta and Exascale
Achitecture Aware Algorithms and Software for Peta and ExascaleAchitecture Aware Algorithms and Software for Peta and Exascale
Achitecture Aware Algorithms and Software for Peta and Exascaleinside-BigData.com
 
TDM Transport over mpls v 1.1
TDM Transport over mpls v 1.1TDM Transport over mpls v 1.1
TDM Transport over mpls v 1.1A Achyar Nur
 
RISC-V 30907 summit 2020 joint picocom_mentor
RISC-V 30907 summit 2020 joint picocom_mentorRISC-V 30907 summit 2020 joint picocom_mentor
RISC-V 30907 summit 2020 joint picocom_mentorRISC-V International
 
Ship Ad-hoc Network (SANET)
Ship Ad-hoc Network (SANET)	Ship Ad-hoc Network (SANET)
Ship Ad-hoc Network (SANET) Benyamin Moadab
 
Crash course on data streaming (with examples using Apache Flink)
Crash course on data streaming (with examples using Apache Flink)Crash course on data streaming (with examples using Apache Flink)
Crash course on data streaming (with examples using Apache Flink)Vincenzo Gulisano
 
FEC & File Multicast
FEC & File MulticastFEC & File Multicast
FEC & File MulticastYoss Cohen
 

Similar to Thesis (20)

Amplification, ROADM and Optical Networking activities at CPqD
Amplification, ROADM and Optical Networking activities at CPqDAmplification, ROADM and Optical Networking activities at CPqD
Amplification, ROADM and Optical Networking activities at CPqD
 
Configuring the communication on FlexRay: the case of the static segment
Configuring the communication on FlexRay: the case of the static segmentConfiguring the communication on FlexRay: the case of the static segment
Configuring the communication on FlexRay: the case of the static segment
 
Klessydra t - designing vector coprocessors for multi-threaded edge-computing...
Klessydra t - designing vector coprocessors for multi-threaded edge-computing...Klessydra t - designing vector coprocessors for multi-threaded edge-computing...
Klessydra t - designing vector coprocessors for multi-threaded edge-computing...
 
Dpdk applications
Dpdk applicationsDpdk applications
Dpdk applications
 
Provisioning Bandwidth & Logical Circuits Using Telecom-Based GIS .
Provisioning Bandwidth & Logical Circuits Using Telecom-Based GIS.Provisioning Bandwidth & Logical Circuits Using Telecom-Based GIS.
Provisioning Bandwidth & Logical Circuits Using Telecom-Based GIS .
 
CRC AND TRANSMIT ERROR REPORT
CRC AND TRANSMIT ERROR REPORTCRC AND TRANSMIT ERROR REPORT
CRC AND TRANSMIT ERROR REPORT
 
Barcelona Supercomputing Center, Generador de Riqueza
Barcelona Supercomputing Center, Generador de RiquezaBarcelona Supercomputing Center, Generador de Riqueza
Barcelona Supercomputing Center, Generador de Riqueza
 
Globecom 2015: Adaptive Raptor Carousel for 802.11
Globecom 2015: Adaptive Raptor Carousel for 802.11Globecom 2015: Adaptive Raptor Carousel for 802.11
Globecom 2015: Adaptive Raptor Carousel for 802.11
 
BFSK RT In FPGA Thesis Pres Jps
BFSK RT In FPGA Thesis Pres JpsBFSK RT In FPGA Thesis Pres Jps
BFSK RT In FPGA Thesis Pres Jps
 
ROLE OF DIGITAL SIMULATION IN CONFIGURING NETWORK PARAMETERS
ROLE OF DIGITAL SIMULATION IN CONFIGURING NETWORK PARAMETERSROLE OF DIGITAL SIMULATION IN CONFIGURING NETWORK PARAMETERS
ROLE OF DIGITAL SIMULATION IN CONFIGURING NETWORK PARAMETERS
 
Vsync track c
Vsync   track cVsync   track c
Vsync track c
 
5378086.ppt
5378086.ppt5378086.ppt
5378086.ppt
 
Achitecture Aware Algorithms and Software for Peta and Exascale
Achitecture Aware Algorithms and Software for Peta and ExascaleAchitecture Aware Algorithms and Software for Peta and Exascale
Achitecture Aware Algorithms and Software for Peta and Exascale
 
TDM Transport over mpls v 1.1
TDM Transport over mpls v 1.1TDM Transport over mpls v 1.1
TDM Transport over mpls v 1.1
 
LTE Air Interface
LTE Air InterfaceLTE Air Interface
LTE Air Interface
 
RISC-V 30907 summit 2020 joint picocom_mentor
RISC-V 30907 summit 2020 joint picocom_mentorRISC-V 30907 summit 2020 joint picocom_mentor
RISC-V 30907 summit 2020 joint picocom_mentor
 
Ship Ad-hoc Network (SANET)
Ship Ad-hoc Network (SANET)	Ship Ad-hoc Network (SANET)
Ship Ad-hoc Network (SANET)
 
Crash course on data streaming (with examples using Apache Flink)
Crash course on data streaming (with examples using Apache Flink)Crash course on data streaming (with examples using Apache Flink)
Crash course on data streaming (with examples using Apache Flink)
 
Zigbee 802-15-4
Zigbee 802-15-4Zigbee 802-15-4
Zigbee 802-15-4
 
FEC & File Multicast
FEC & File MulticastFEC & File Multicast
FEC & File Multicast
 

Thesis

  • 1. PERFORMANCE ANALYSIS OF A NETWORK BASED, ULTRAFAST CENTRALIZED FAULT IDENTIFICATION AND LOCATION SYSTEM Advisor: Dr. Ming Yu Co-advisor: Dr. Michael Steurer Committee member: Dr. Hui Li 7/12/2016 1 Presenter: Shravan Tamaskar M.S. Thesis Defense: 6 June 2016
  • 2. Outline  Overview – Motivation – Objective and key contribution  Introduction to Centralized Fault identification and Location (CFL) system architecture  Performance modeling of CFL system  Analyzing the factors affecting the CFL system performance  Validation: CFL demonstration and implementation  Conclusion and Future work 7/12/2016 2
  • 3. Motivation: CFL  Fault management in medium voltage direct current (MVDC) shipboard power system (SPS) aimed to be accomplished in 8 ms 7/12/2016 3  A need for fast fault identification system necessary  This led to the development of centralized fault identification and location (CFL) system 8 ms
  • 4. Objective ■ To develop a testbed for an ultrafast fault identification system for the MVDC SPS ■ To model, analyze and validate the performance of the CFL system ■ To analyze the scaling and the factors affecting the CFL system performance Key Contribution ■ Modeling of – EtherCAT Frame – CFL decision time ■ Scaling of CFL system based on – Frame – Cycle time ■ Performance parameters – Topology – Preliminary noise analysis ■ Developed a CFL testbed and implemented using different system configurations 7/12/2016 4
  • 5. 7/12/2016 5 Fault Management in MVDC SPS Fault Management in MVDC SPS Rapid fault identification Fault Identification Fault Clearing highly-coordinated interaction Detect and localize fault Re-energize system De-energize system Isolate faulted segment Detect & locate 8 ms
  • 6. Introduction to CFL architecture ■ CFL architecture ■ Differential protection scheme ■ CFL process description 7/12/2016 6
  • 7. CFL architecture 7/12/2016 CAPS, FSU 7 CS- Cable Section PGM- Power Generation Module Disconnect Switch CS1 CS2 CS3 CS4 CS5CS6CS7 CS8 PG M PG M Load Load CFL Power System
  • 8. No Fault Differential protection scheme 7/12/2016 CAPS, FSU 8 Operates based on Percentage Differential Protection (PDP) scheme CS- Cable Section DS- Disconnect Switch LIF test case Slope diagram of protection scheme DSA DSA DS B DS BCS CS Normal Operation During Fault A B Time msΔI +Ia -Ib | 𝑛=2 𝑛 𝐼 𝑛| − 𝑆 . 𝑛=2 𝑛 |𝐼 𝑛| ≥ 𝐼𝑚𝑖𝑛
  • 9. 7/12/2016 CAPS, FSU 9  Main parts of CFL system  A master unit with fault protection algorithm  Several slave units that perform data acquisition and send digitized current data to master unit for decision making  A communication (EtherCAT) protocol governing master- slave topology Master (Algorithm) Line topology Slave nSlave 1 Slave 2 Generic CFL system Architecture EtherCAT Hardware CAPS Capability In-use Master 1 1 I/O nodes 20 9 Slaves 6 6
  • 10. 7/12/2016 10 Master Condition check Counter Increment Counter threshold Trip True slave1slave n False EtherCAT Frame YesNo CFL process description Data signal Logic signal Reset counter
  • 11.  Frame modeling  Cycle time modeling  Decision time 1. RTDS processing 2. Hardware sync 3. Beckhoff processing 7/12/2016 11 Performance Modeling
  • 13. Frame Modeling 7/12/2016 13 𝐷𝐺 𝑝𝑙 = (𝑛 𝐹𝑂 x 𝐿 𝐹𝑂 + 𝑛 𝐴𝐼 x 𝐿 𝐴𝐼 + 𝑛 𝐷𝑂 x 𝐿 𝐷𝑂 ) 𝐿 𝐷𝐺 = 𝐷𝐺=1 𝐷𝐺 (𝐷𝐺 𝐻 + 𝐷𝐺 𝑝𝑙 + 𝐷𝐺 𝑤𝑘𝑐 ) 𝐿 𝐹𝑟𝑎𝑚𝑒 = 𝐸 𝑇𝑦𝑝𝑒 + 𝐿 𝑐𝑚𝑑 + 𝐸𝑐𝑎𝑡 𝐻 + 𝐿 𝐷𝐺 Description Abbreviation Size (Byte) EtherType 𝐸 𝑇𝑦𝑝𝑒 2 Commands 𝐿 𝑐𝑚𝑑 10 EtherCAT Header 𝐸𝑐𝑎𝑡 𝐻 2 Datagram Header 𝐷𝐺 𝐻 10 No. of Slaves 𝑛 𝑠𝑙𝑎𝑣𝑒𝑠 6 No. of Analog Input channel 𝑛 𝐴𝐼 No. of Digital Output channel 𝑛 𝐷𝑂 No. of Fiber Optic connecter 𝑛 𝐹𝑂 Size of Analog Input 𝐿 𝐴𝐼 4 Size of Digital Output 𝐿 𝐷𝑂 3 Size of Fiber Optic connecter 𝐿 𝐹𝑂 2 Datagram working counter 𝐷𝐺 𝑤𝑘𝑐 2
  • 14. Simulated number of frames 7/12/2016 14 𝑇𝑓𝑟𝑎𝑚𝑒 = 𝐿 𝑓𝑟𝑎𝑚𝑒 × 8 𝑏𝑤 Frame transmission time nFrame = ceiling ( 𝐿𝑒𝑛𝑔𝑡ℎ 𝑜𝑓 𝐹𝑟𝑎𝑚𝑒 1500 ) Time taken by the controller to transmit the bits in the frame
  • 15. Cycle Time 7/12/2016 15 𝑇𝑐 = 2 × (( 𝑁 𝑇 + 1) × 𝑇𝑝+ 𝑇 𝑀 𝑓 + (𝑁 𝑇 × 𝑇𝑆 𝑓 ) + 𝑇𝑐 𝑝 ) Master Slave 1 Slave 2 Slave n Defined as the time necessary for the exchange of input/output data between the controller and all networked devices once Simulated cycle time Measured cycle timeMeasured cycle time 20.22 µs 16.73 µs Number of slaves Minimumcycletime(µs) 20.96 µs
  • 16. Communication System Power System CFL Testbed 7/12/2016 CAPS, FSU 16 RTDS SPS Simulation Slaves AI, DO Master (Protection algorithm) Analog Signals Digital Signals Simulates Fault Initiates fault clearing sequence EtherCAT Packet Simulation timestep- 50 µs Cycle Time 50 µs M ss s CS4 CS8 PGM Load PGM Load
  • 17. CFL decision time- RTDS processing 7/12/2016 17 tRTDS = nproc step x tSimulationTimeStep Time taken by RTDS (tRTDS) to process the simulation logic and generate a signal which goes out of RTDS analog output Decision time • RTDS processing • Beckhoff processing • Synchronization mismatch
  • 18. CFL Decision Time- Beckhoff Processing 7/12/2016 18 The time taken by the beckhoff (tbeckhoff) system to read the signals and compute the algorithm and generate a response signal. Cycle time (tct) 50 µsCycle time (tct) 100 µs tbeckhoff = (niter + 1) x tct 600 µs 5 iterations (niter) for fault identification, (n+1) 6 timesteps fault initiation signal fault detection by CFL 300 µs Yellow - Blue-
  • 19. CFL Decision Time- Synchronization mismatch 7/12/2016 19 Additional time added to the system operation due to simulation delays and delays in the logic processing and hardware interfacing tmismatch = thsm+ tbpd RTDS SPS Simulation Slaves AI, DOAnalog Signals No sync Beckhoff processing delay (tbpd) Hardware Synchronization Mismatch (thsm) Worst timing 2 cycle time 1 cycle time Best timing
  • 20. CFL Decision Time 7/12/2016 20 Decision time is the sum of all the individual timings to detect a fault in the SPS td = tRTDS + tbeckhoff + tmismatch Fault initialization RTDS output to slaves CFL decision out RTDS trip signal Time (µs)
  • 21. CFL Decision Time 7/12/2016 21 0 100 200 300 400 500 600 700 800 900 Total RTDS Processing RTDS Processing Hardware Sync Beckhoff error Cycle 1 Cycle 2 Cycle 3 Cycle 4 Cycle 5 (n+1)th cycle RTDS Processing time (µs) CFL Timing Analysis- Individual Split-up Hardware sync Beckhoff delay
  • 22. 1. Topology – Line – Ring 2. Jitter 3. Bandwidth 4. Network propagation time 5. Noise – AWGN / SNR – Noise on CFL System 7/12/2016 22 Performance parameters
  • 23. Performance parameters- Topology 7/12/2016 23 Master Slave 1 Slave 2 Slave n Ring topology Additional/ return path Master Slave 1 Slave 2 Slave n Line topology Return path Tcycle = Tframe + Tnetwork Advantages of Ring topology 1. Resilient to 1 cable cut condition 2. Additional path for packet flow 3. Better cycle time for large systems Theoretical minimum cycle time
  • 24. Performance parameters- Jitter 7/12/2016 24 J = |Tc − Tcm| TC - set cycle time (eg. 50 µs) Tcm - measured cycle time Causes- • Network congestion • Improper queuing • Configuration errors Jitter can be described as latencies in the network components which may result in the variation of the cycle time Jitter (simulated) per slave during the execution of the CFL system configured at 50 µs
  • 25. Performance parameters- Bandwidth 7/12/2016 25 NRB = |Tc − MCT| Tc × 100 MCT- Minimum cycle time TC – set cycle time value NRB- Non-realtime bandwidth Line Topology Theoretical extrapolation showing the comparison of Fast Ethernet and gigabit Ethernet The affect of bandwidth on cycle time with respect to slaves Number of slaves Minimumcycletime(µs) Line Topology Number of slaves Minimumcycletime(µs) Fast Ethernet 100 Mbps Gigabit Ethernet 1 Gbps
  • 26. Performance parameters- Network propagation time 7/12/2016 26 • Forwarding delays produced by slave devices • Cable propagation delays Theoretical network propagation time networkpropagationtime(µs) Number of slaves
  • 27. Performance parameters- Noise 7/12/2016 27 Additive White Gaussian noise SNR = 20 × log10( 𝑉 𝑠𝑖𝑔𝑛𝑎𝑙 𝑉 𝑛𝑜𝑖𝑠𝑒 ) Higher the SNR Lower the noise in the signal Better the measurement reading Definition: Noise is a random, undesirable energy that enters the communication system via the communicating medium and interferes with the transmitted message Preliminary analysis: Focused on the effect of noise on the CFL detection before the fault occurs. Question: Can noise create a false identification? Noise Signal Receiver Signal + Noise
  • 28. Performance parameters- Noise: CASE 1 7/12/2016 28 CASE 1: Noise in one measurement node measurement node Timestep
  • 29. Performance parameters- Noise CASE 2 7/12/2016 29 CASE 2: Noise in both the measurement nodes measurement node Timestep
  • 30. CFL demonstration and implementation Norbert Doerry’s MVDC SPS architecture 7/12/2016 30
  • 31. SPS model 7/12/2016 31 1 MW PGM is interfaced to 5 kV MVDC bus CS1 CS2 CS3 CS4 CS5CS6CS7 CS8 F I O FIO F IO F I O F I O Master F I O LOADInput signals (Current) from RTDS to Analog Input Output signal from Digital Output to RTDS GTDI Master Slave Connection (Fiber) Disconnect Switch CS- Cable Section I –Analog Input Terminal O–Digital Output Terminal F –Fiber optic converter junction F I O Slave UnitMMC LOAD MMC 1 PG M PG M Load Load
  • 32. CFL Demonstration 7/12/2016 CAPS, FSU 32 t0 – RTDS simulation logic processing t1 – CFL decision time t2 – synchronization mismatch and simulation logic processing CHIL implementation of CFL system t0 t1 t2 750 µs time (ms) 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 time (ms) Fault Simulation RTDS trip signal
  • 33. Implementation Condition Type Time (µs) Fault impedance Low impedance fault 300 High impedance fault Power system configuration Open ring Closed ring Loading condition 0.544 MW 0.125 MW Operating modes VSM- CSM VSM- VSM 7/12/2016 33 VSM- Voltage source mode CSM- Current source mode
  • 34. ■ Models to determine the performance and scaling of CFL system were developed ■ Analyzed and discussed the factors affecting the CFL performance ■ The effectiveness of the model has been verified. ■ A CFL, based on percentage differential protection, demonstrates fault detection time of ~300 µs. ■ The CFL system was tested for various system operating conditions and the results demonstrate its desired performance ■ The ultrafast fault identification system paves the way to accomplish fault management in the desired 8 ms time frame 7/12/2016 34 Conclusion
  • 35. ■ Hardware Implementation of a ring topology ■ Validating the system resiliency for cable cut condition ■ System level control ■ Exhaustive Noise analysis ■ Integrating multiple CFL units 7/12/2016 35 Future Work
  • 36. References 1. Shravan Tamaskar, Harsha Ravindra, Mike Sloderbeck, Ruturaj Soman, and Michael Steurer. "CHIL-based Demonstration of Centralized Fault Location Strategy for a MVDC Shipboard Power System." 2. Qiu Deng, Xing Liu, Ruturaj Soman, Michael Steurer, and Roger A. Dougal. "Primary and backup protection for fault current limited MVDC shipboard power systems." In Electric Ship Technologies Symposium (ESTS), 2015 IEEE, pp. 40-47. IEEE, 2015. 3. Michael J. Thompson, "Percentage restrained differential, percentage of what?." In Protective Relay Engineers, 2011 64th Annual Conference for, pp. 278-289. IEEE, 2011. 4. https://www.ethercat.org/ 5. http://infosys.beckhoff.com/ 6. Ziyuan Cai, and Ming Yu. "Modeling and Simulation of a Real-time Ethernet Protocol for Smart Grids." International Journal Of Intelligent Control And Systems 17, no. 3 (2012): 69-78. 7. Mladen Knezic, Branko Dokic, and Zeljko. Ivanovic. "Topology aspects in EtherCAT networks." In Proceedings of 14th International Power Electronics and Motion Control Conference EPE- PEMC 2010. 2010. 8. B. P. Lathi (1968). Communication systems. New York, Wiley. 9. J. A. Betts (1970). Signal processing, modulation and noise. London, English Universities. 7/12/2016 36

Editor's Notes

  1. Power system model, applying a fault identification system on the PS Overlay of CFL system
  2. Operating current is the vector sum of all the currents Restraint current is the magnitude sum of all the currents in the particular system.
  3. Experimental and theory differentiate in slides
  4. Master configuration- Understands the number of slaves connected in the topology, The function of each slave (read/write,/ read&write)
  5. Within the frames, the Working Counter enables the information in each datagram to be monitored for consistency. Every node that is addressed by the datagram and whose memory is accessible increments the Working Counter automatically. The master is then able to cyclically confirm if all nodes are working with consistent data. If the Working Counter has a different value than it should, the master does not forward this datagram’s data to the control application. The master device is then able to automatically detect the reason for the unexpected behavior with help from status and error information from the nodes as well as the Link Status.
  6. Graph helps us understand the number of EtherCAT frames required wrt number of slaves in the system
  7. Time taken by the controller to transmit the bits in the frame Why the need?
  8. This time is defined as the time necessary for the exchange of input/output data between the controller and all networked devices once, and is highly dependent on the used network topology. I/O read/write A/D conversion Frame transmission Network propagation Why the need? Round trip cycle time can help in understanding of the effects of number of slaves and cycle time 𝑇 𝑓 = ( 𝑁 𝐹 × 𝑆 𝐹𝐻 + 𝑆 𝐼𝐹𝐺 + 𝑁 𝑇 × 𝑆 𝑇𝐻 + 𝑆 𝑇 )× 𝑇 𝐵
  9. Write abbriviations
  10. Units
  11. Tframe = Lframe x 8 / bw Tnode = tMMp + tMMf + 2 (tRx + tTx) TEndNode = tMMP + tRx + tTx Tnetwork = Tcable + Tmaster + (n-1) x Tnode + tEndNode Tnetwork = Tcable + Tmaster + ∑ Tnode
  12. NRB is evaluated as the percentage of bandwidth that may be used for non real time traffic within a cycle
  13. White noise is assumed to be a random signal with a constant power spectral density. SNR- Noise 10 ~ 30% 15 ~ 20% 20 ~ 10%
  14. Preliminary analysis
  15. Change the plot
  16. Consistent format for references