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POWERLINE COMMUNICATIONS FOR ENABLING SMART GRID APPLICATIONS

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

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POWERLINE COMMUNICATIONS FOR ENABLING SMART GRID APPLICATIONS

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  1. 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

  2. Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed 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

  3. Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed Task Deliverables

  4. Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed Smart Grid: Big Picture Long distance communication : access to isolated houses Real-Time : Customers profiling enabling good predictions in demand = no need to use an additional power plant Micro- production: better knowledge of energy produced to balance the network Demand-side management : boilers are activated during the night when electricity is available Smart building : significant cost reduction on energy bill through remote monitoring Any disturbance due to a storm : action can be taken immediately based on real-time information Security features Fire is detected : relay can be switched off rapidly Smart car : charge of electrical vehicles while panels are producing Source: ETSI

  5. Built for unidirectionalflow of power and notfor bidirectionalcommunications Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed Power Lines High Voltage (HV)33 kV – 765 kV Medium Voltage (MV)1 kV – 33 kV Low Voltage (LV)under 1 kV Concentrator(Transformer) Source: ÉlectricitéRéseau Dist. France (ERDF)

  6. Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed Powerline Communications 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

  7. Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed 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

  8. Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed Narrowband PLC Impulsive Noise Rx Receiver Increases with widespread deployment Dominant in outdoor PLC

  9. Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed Cyclostationary Noise Modeling Proposed model uses three filters [Nassar12] Cyclostationary Gaussian Model[Katayama06] Measurement data from UT/TI field trial Demux Period is one halfof an AC cycle s[k] is zero-mean Gaussian noise Adopted by IEEE P1901.2 narrowband PLC standard

  10. Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed Asynchronous Noise Modeling Dominant Interference Source Ex. Rural areas, industrial areas w/ heavy machinery Middleton Class ADistribution [Nassar11] Impulse rate lImpulse duration m Homogeneous PLC Network li = l, mi= m, g(di) = g0 Ex. Semi-urban areas, apartment complexes Middleton Class ADistribution [Nassar11] General PLC Network Ex. Dense urban and commercial settings li, mi, g(di) = gi Gaussian MixtureModel [Nassar11] Middleton Class A is a special case of the Gaussian Mixture Model.

  11. Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed Asynchronous Noise • Sparse in time domain • 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 ~10dB ~6dB time Transmission places 0-3 bits at each tone (frequency). At receiver, null tone carries 0 bits and only contains impulsive noise.

  12. Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed 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

  13. Task Summary | Background | PLC Noise Modeling and Mitigation | PLC Testbed Our PLC Testbed 1x1 Testbed

  14. 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.

  15. Thank you for your attention… Questions?

  16. Backup Slides

  17. PLC Noise Scenarios time

  18. Cyclostationary Noise Noise Sources Noise Trace

  19. Uncoordinated Interference Results Homogeneous PLC Network General PLC Network

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