Powerline Communications for Enabling Smart Grid Applications

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POWERLINE COMMUNICATIONS FOR
ENABLING SMART GRID APPLICATIONS
Task ID: 1836.063
Prof. Brian L. Evans
Wireless Networking and Communications Group
Cockrell School of Engineering
The University of Texas at Austin
bevans@ece.utexas.edu
http://www.ece.utexas.edu/~bevans/projects/plc
May 3, 2012
Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed
1
Task Description:
Improve powerline communication (PLC) bit rates for monitoring/controlling
applications for residential and commercial energy uses
Anticipated Results:
Adaptive methods and real-time prototypes to increase bit rates in PLC networks
Principal Investigator:
Prof. Brian L. Evans, The University of Texas at Austin
Current Students (with expected graduation dates):
Ms. Jing Lin
Ph.D. (May 2014)
Mr. Yousof Mortazavi
Ph.D. (Dec. 2012)
Mr. Marcel Nassar
Ph.D. (Dec. 2012)
Mr. Karl Nieman Ph.D. (May 2014)
Industrial Liaisons:
Dr. Anand Dabak (TI), Mr. Leo Dehner (Freescale), Mr. Michael Dow
(Freescale), Mr. Frank Liu (IBM) and Dr. Khurram Waheed (Freescale)
Starting Date: August 2010
Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed
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Task Deliverables
Date
Tasks
Dec 2010
Uncoordinated interference in narrowband PLC:
measurements, modeling, and mitigation
May 2011
Single-transmitter single-receiver (1x1) PLC testbed
Dec 2011
Narrowband PLC channel and noise:
measurements and modeling
On-going
Two-transmitter two-receiver (2x2) PLC testbed
Narrowband PLC noise mitigation
Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed
3
Smart Grid: Big Picture
Real-Time :
Customers profiling
enabling good
predictions in demand =
no need to use an
additional power plant
Long distance
communication :
access to isolated
houses
Micro- production:
better knowledge of
energy produced to
balance the network
Demand-side
management : boilers
are activated during the
night when electricity is
available
Any disturbance due to a
storm : action can be taken
immediately based on realtime information
Smart building :
significant cost reduction
on energy bill through
remote monitoring
Smart car : charge of
electrical vehicles while
panels are producing
Security features
Fire is detected : relay
can be switched off
rapidly
Source: ETSI
Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed
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Power Lines
Built for unidirectional
flow of power and not
for bidirectional
communications
Low Voltage (LV)
under 1 kV
High Voltage (HV)
33 kV – 765 kV
Medium Voltage (MV)
1 kV – 33 kV
Concentrator
(Transformer)
Source: Électricité Réseau
Dist. France (ERDF)
Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed
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Powerline Communications
Category
Freq. Band
Bit Rate
Applications
Ultra narrowband
0.3 – 3.0 kHz
~100 bps
• Automatic meter reading
• Outage detection
• Voltage monitoring
Narrowband
3 – 500 kHz
~500 kbps
• Device-specific billing
• Smart energy management
Broadband
1.8 – 250 MHz
~200 Mbps • Home area networks
Narrowband PLC systems
• Bidirectional communication over
MV/LV lines between local utility
and customers
• Industry standards: G3, PRIME
• International standards: G.hnem,
IEEE P1901.2
Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed
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Narrowband PLC Systems
• Problem: Non-Gaussian impulsive noise is primary
limitation to PLC communication performance yet traditional
communication system design assumes noise is Gaussian
• Goal: Improve communication performance in impulsive
noise (i.e. increase bit rate and/or reduce error rate)
• Approach: Statistical modeling of impulsive noise
• Solution: Receiver design to mitigate impulsive noise
Parametric
Nonparametric
Listen to environment
No training necessary
Find model parameters
Learn statistical model from
communication signal structure
Use model to mitigate noise
Exploit sparsity to mitigate noise
Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed
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Narrowband PLC Impulsive Noise
Cyclostationary Noise
Asynchronous Noise
Example: rectified power supplies
Example: uncoordinated interference
Rx Receiver
Dominant in outdoor PLC
Increases with widespread deployment
Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed
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Cyclostationary Noise Modeling
Measurement data
from UT/TI field trial
Cyclostationary
Gaussian Model
Proposed model uses
three filters [Nassar12]
[Katayama06]
Demux
Period is one half
of an AC cycle
s[k] is zero-mean
Gaussian noise
Adopted by IEEE P1901.2
narrowband PLC standard
Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed
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Asynchronous Noise Modeling
Dominant Interference Source
Impulse rate l
Impulse duration m
Ex. Rural areas,
industrial areas w/
heavy machinery
Middleton Class A
Ex. Semi-urban
areas, apartment
complexes
Middleton Class A
Ex. Dense urban
and commercial
settings
Gaussian Mixture
Distribution [Nassar11]
Homogeneous PLC Network
li = l, mi = m, g(di) = g0
Distribution [Nassar11]
General PLC Network
li, mi, g(di) = gi
Model [Nassar11]
Middleton Class A is a special case of the Gaussian Mixture Model.
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Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed
Asynchronous Noise
• Sparse in time domain
-1
10
~10dB
time
~6dB
• Learn statistical model
• Use sparse Bayesian
learning (SBL)
• Exploit sparsity in time
domain [Lin11]
• SNR gain of 6-10 dB
• Increases 2-3 bits per tone
for same error rate - OR • Decreases bit error rate by
10-100x for same SNR
Symbol Error Rate
-2
10
-3
10
-4
10
No cancellation
SBL w/ null tones
-5
SBL w/ all tones
10
-10
-5
0
SNR (dB)
5
10
Transmission places 0-3 bits at each tone
(frequency). At receiver, null tone carries 0
bits and only contains impulsive noise.
Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed
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Our PLC Testbed
• Quantify application performance vs. complexity tradeoffs
• Extend our real-time DSL testbed (deployed in field)
• Integrate ideas from multiple narrowband PLC standards
• Provide suite of user-configurable algorithms and system settings
• Display statistics of communication performance
• 1x1 PLC testbed (completed)
• Adaptive signal processing algorithms
• Improved communication performance 2-3x on indoor power lines
• 2x2 PLC testbed (on-going)
• Use one phase, neutral and ground
• Goal: Improve communication performance by another 2x
Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed
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Our PLC Testbed
Hardware
Software
• National Instruments (NI) controllers stream • Real-time system runs transceiver
data
algorithms
• NI cards generates/receives analog signals
• Desktop PC running LabVIEW is used
• Texas Instruments (TI) front end couples to
as an input and visualization tool to
power line
display important system parameters.
1x1 Testbed
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Our Peer-Reviewed Publications
Tutorial/Survey Article
• M. Nassar, J. Lin, Y. Mortazavi, A. Dabak, I. H. Kim and B. L. Evans, “Local Utility
Powerline Communications in the 3-500 kHz Band: Channel Impairments, Noise,
and Standards”, IEEE Signal Processing Magazine, Special Issue on Signal Processing
Techniques for the Smart Grid, Sep. 2012.
Conference Publications
• M. Nassar, A. Dabak, I. H. Kim, T. Pande and B. L. Evans, “Cyclostationary Noise
Modeling In Narrowband Powerline Communication For Smart Grid Applications”,
Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Proc., Mar. 2012, Kyoto, Japan.
• M. Nassar, K. Gulati, Y. Mortazavi, and B. L. Evans, “Statistical Modeling of
Asynchronous Impulsive Noise in Powerline Communication Networks”, Proc. IEEE
Int. Global Communications Conf., Dec. 2011, Houston, TX USA.
• J. Lin, M. Nassar and B. L. Evans, “Non-Parametric Impulsive Noise Mitigation in
OFDM Systems Using Sparse Bayesian Learning”, Proc. IEEE Int. Global
Communications Conf., Dec. 2011, Houston, TX USA.
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Thank you for your attention…
Questions?
15
Backup Slides
16
PLC Noise Scenarios
Background Noise
Asynchronous
Impulsive Noise
Cyclostationary Noise
-50
-100
-150
•
•
•
•
time
0
100
200
300
Frequency (kHz)
400
500
Spectrally shaped noise
Decreases with frequency
Superposition of lowerintensity sources
Includes narrowband
interference
•
•
•
•
Cylostationary in time and
frequency
Synchronous and
asynchronous to AC main
frequency
Comes from rectified and
switched power supplies
(synchronous), and electrical
motors (asynchronous)
Dominant in narrowband PLC
•
•
•
•
•
Impulse duration from
micro to millisecond
Random inter-arrival time
50dB above background
noise
Caused by switching
transients and
uncoordinated interference
Present in narrowband
and broadband PLC
17
Cyclostationary Noise
Noise Sources
Noise Trace
18
Uncoordinated Interference Results
Homogeneous PLC Network
General PLC Network
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