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Simulation and Analysis of Wireless Mesh Network In Smart Grid / Advanced Metering Infrastructure

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Title: Simulation and Analysis of Wireless Mesh Network In Smart Grid / Advanced Metering Infrastructure


1
  • Simulation and Analysis of Wireless Mesh Network
    In Smart Grid / Advanced Metering Infrastructure
  • Masters Thesis
  • Philip Huynh
  • Spring 2011

2
Outline of the Talk
  • Introduction
  • Related work
  • Real-time Smart Grid Meter Data Collection using
    Hybrid WiMAX/Wi-Fi Networks
  • Smart Grid Wireless Infrastructure Planning
    (SG-WIP) Tool.
  • Simulation Results of SG-SIM
  • Lessons Learned
  • Future Direction
  • Conclusion

3
Introduction
  • What is the Advanced Metering Infrastructure
    (AMI)?
  • The need to collect metering data in real-time
  • Save the material usage for the electric power
    generation by correctly predict the load demand
    and build the load profile

4
Wireless Mesh Network for AMI
  • High scalable and performance networks
  • Can deploy on the large service areas urban,
    suburb
  • Low cost installation and maintenance
  • Secured networks IEEE802.16, IEEE 802.11s

Wi-Fi mesh networks with WiMAX backhaul
Wireless technologies (source Intel)
5
CSU AMI Infrastructure
6
Related Work
  • Wireless Mesh Networks A Survey AWW05
  • The author presented many open research issues
    needed to be solved such as scalability,
    self-organization and self-configuration,
    security, network integration. The critical
    factors influencing protocol design were
    discussed for improvement objectives.
  • The Nominal Capacity of Wireless Mesh Networks
    JS03
  • The authors shown that for WMNs the throughput
    of each node decreases as O(1/n), where n is
    total number of nodes in the network. Moreover,
    for a given topology and the set of active nodes,
    the upper bounds on the throughput of any node
    can be exactly calculated.
  • Architecture and Algorithms for an IEEE
    802.11-based Multi-channel Wireless Mesh Network
    RC05
  • The author proposed a novel multi-channel WMN
    architecture that effectively addresses the
    bandwidth problem by fully exploiting
    non-overlapped radio channels that the IEEE
    802.11 standards make available.

7
Related Work (2)
  • Multi-Channel Mesh Networks Challenges and
    Protocols KSCV06
  • The authors considered the use of multi-channel
    to improve the throughput of Wireless Mesh
    Network (WMN). The main challenges were
    highlighted and two link-layer protocols were
    presented for utilizing multiple channels
  • Capacity of Grid-Oriented Wireless Mesh
    Networks ANMK08
  • The author presented an analytical framework for
    determining the nominal capacity of multi-radio
    multi-channel Wireless Mesh Network (WMN). As the
    research conclusion, the effects of WMN design
    parameters such as network topology, network
    size, routing methods, channel assignment schemes
    etc. are interlinked and a judicious selection is
    essential to maximize capacity.
  • Coverage and capacity of a wireless mesh
    network HWC05
  • The authors proposed a scalable multi-channel
    ring-based WMN architecture and developed an
    analytical framework to evaluate the capacity and
    coverage of such a network.

8
Related Work (3)
  • The IEEE 802.11s Extended Service Set Mesh
    Networking Standard CK08
  • The author presented how the developing IEEE
    802.11s ESS Mesh Networking Standard draft
    addresses technical challenges of the pervasive
    development of wireless mesh networks (WMNs), the
    efficient allocation of mesh resources (routing
    and MAC layers), the protection of network
    resources (security and power savings), and the
    elimination of spatial bias (congestion control).
  • An Improved IEEE 802.16 WiMAX Module for the
    ns-3 Simulator IPGT10
  • The authors presented the new features and
    enhancements that were integrated within the ns-3
    WiMAX module. These proposed features can make
    easier and more realistic the evaluation and
    design of WiMAX systems.

9
Challenges Approach
  • Challenges in Design and Deployment AMI Network
    using WMN
  • How to evaluate the network performance hundred
    thousands of smart meters, complicated
    architecture
  • How the scalability affects to the performance
  • Approach
  • Develop a Network Topology Planning Tool
  • Develop a Network Simulator for AMI Communication
    Network
  • Simulate the network model and Analyze the
    results
  • Goals
  • Develop techniques and tools to evaluate the
    performance of AMI WMN.

10
Hybrid WiMAX/Wi-Fi Network Model
(a)
(b)
Hybrid WiMAX/Wi-Fi Network Model
(a) Example of WiMAX network (WAN)
(b) Example of Wi-Fi mesh network (NAN)
11
SG-WIP Tool
  • A mashup that overlays the wireless
    infrastructure and GIS data (street light poles,
    housing units) on the Google Maps
  • Visually planning the Antenna mounting place for
    the WiMAX/Wi-Fi network
  • Export the network topology as XML file for
    further research
  • Can be integrated to the network simulator

12
SG-WIP GUI
GUI includes components Main Menu, Network
Topology Overlay, Google Maps, and Topology
Information Panel.
13
SG-WIP Navigating Topologies
Metropolitan Area Network (MAN) using WiMAX
point-to-multi point grid 10x10, 10 km x 10 km
(WxH)
Neighborhood Area Network (NAN) using Wi-Fi mesh
grid 10x10, 1 km x 1 km (WxH)
14
SG-WIP Exporting Topology
Local Area Network (LAN) using Wi-Fi
point-to-multi point square, 100 m x 100 m (WxH)
Exporting the LAN topology as an XML file
15
SG-WIP Changing Antennae Position
(a)
(b)
WiMAX base stations antennae (a) Before
changing, location at (5, 5) (b) After changing,
location at (6, 9)
16
SG-WIP Code
  • // Calculate the center point of the Colo Sprgs
    boundary house/building units
  • // Show the map of Colorado Springs
  • var csCenter getCenter(new GeoRectangle(csSW,
    csNE))
  • var latlng new google.maps.LatLng(csCenter.Latit
    ude, csCenter.Longitude)
  • // Map's options
  • var myOptions
  • zoom startZoom,
  • center latlng,
  • mapTypeId google.maps.MapTypeId.ROADMAP,
  • mapTypeControl true,
  • navigationControl true,
  • scaleControl true
  • // Map object instance
  • map new google.maps.Map(document.getElementById(
    "map-canvas"), myOptions)
  • // Add the network topology as an overlay object
    on map
  • polygon new google.maps.Polygon(
  • paths paths,
  • // Handle the Click event on the network topology
  • google.maps.event.addListener(polygon, 'click',
    function(event)
  • var lat event.latLng.lat()
  • var lng event.latLng.lng()
  • Network.clickEvent(lat, lng)
  • // Geographical coordinates helper functions
  • //This uses the haversine formula to calculate
    great-circle distances between
  • //the two points that is, the shortest distance
    over the earths surface
  • // giving an as-the-crow-flies distance between
    the points (ignoring any hills!).
  • function distance_between(lat1, lon1, lat2,
    lon2)
  • var dLat (lat2-lat1)degrees_to_radians
  • var dLon (lon2-lon1)degrees_to_radians
  • var a Math.sin(dLat/2) Math.sin(dLat/2)
  • Math.cos(lat1degrees_to_radians)
    Math.cos(lat2degrees_to_radians)
  • Math.sin(dLon/2) Math.sin(dLon/2)
  • var c 2 Math.atan2(Math.sqrt(a),
    Math.sqrt(1-a))
  • var d earth_radius c
  • return d

17
SG-SIM Simulator
  • Implements the proposed hybrid WiMAX/Wi-Fi
    Network Model on NS-3 platform
  • The network simulator NS-3 is
  • Open source project
  • Popular and accepted by network research
    community
  • Parameters of the Simulator
  • Network types WAN, MAN, NAN, LAN
  • Number of nodes, Transmission Rate
  • Others network initialization time,

18
SG-SIM Code
  • // Install node location for WiMAX base station,
    gateways
  • MobilityHelper mobility
  • mobility.SetPositionAllocator ("ns3GridPositionA
    llocator",
  • "MinX", DoubleValue (0.0),
  • "MinY", DoubleValue (0.0),
  • "DeltaX", DoubleValue (1000),
  • "DeltaY", DoubleValue (1000),
  • "GridWidth", UintegerValue (5),
  • "LayoutType", StringValue ("RowFirst"))
  • mobility.SetMobilityModel ("ns3ConstantPositionM
    obilityModel")
  • mobility.Install (bsNodes)
  • mobility.Install (ssNodes)
  • // Create a packet sink to receive these packets
  • Address sinkLocalAddress (InetSocketAddress
  • (Ipv4AddressGetAny (), 50000))
  • PacketSinkHelper sinkHelper ("ns3UdpSocketFactor
    y",
  • sinkLocalAddress)
  • ApplicationContainer sinkApp sinkHelper.Install
    (serverNode)

// Install the app on the SS nodes for (int i0
iltnbSS i) // build the application
PtrltSgOnOffApplicationgt sgOnOff
CreateObjectltSgOnOffApplicationgt()
sgOnOff-gtSetAttribute ("Protocol", StringValue
("ns3UdpSocketFactory"))
sgOnOff-gtSetAttribute ("OnTime",
RandomVariableValue (ConstantVariable (1)))
sgOnOff-gtSetAttribute ("OffTime",
RandomVariableValue (ConstantVariable (0)))
sgOnOff-gtSetAttribute ("DataRate",
DataRateValue (DataRate (m_packetDataRate)))
sgOnOff-gtSetAttribute ("PacketSize",
UintegerValue (lenPacket))
sgOnOff-gtSetAttribute ("Remote",
remoteAddress) sgOnOff-gtSetStartTime
(Seconds (start 0.000001i)) ssNodes.Get
(i)-gtAddApplication(sgOnOff)
19
Simulation Experiments
  • Experiment Design Vision
  • Evaluate the performance of AMI Infrastructure
  • How the scalability impacts to the performance
  • Measure the performance of network with many
    source nodes at the specific Constant Bit Rate
    (CBR)
  • Confirm to smart meter density analysis (using
    SG-WIP)

20
LAN Simulation Results
  • Tx packets Rx packets
  • Total processing delay increases linearly with
    the number of smart meter

21
NAN Simulation Results
  • Tx packets Rx packets
  • Total processing delay increases rapidly with the
    number of mesh routers.

22
MAN Simulation Results
  • Tx packets Rx packets
  • Total processing delay converges to 930 msecs. It
    caused by 5 msecs fixed frame time in IEEE 802.16
    standard.

23
MAN Simulation Results (2)
Impact on the network performance by aggregating
meter data at the gateway
  • Tx packets Rx packets when number of meter
    packets lt 16
  • Tx packets gt Rx packets when number of meter
    packets gt 16 (caused by UDP packet
    fragmentation)
  • Total processing delay increases slowly with the
    number of meter packets

24
WAN Simulation Results
  • The total processing time was linearly increased
    with the length of the optical cables.

25
Lessons Learned
  • Development of SG-WIP Tool
  • Challenges in testing and debugging source code
    for Web application (used PHP/JavaScript)
  • GIS Information Acquisition time consuming
    process
  • Development of SG-SIM Simulator
  • Found the bug in NS-3 WiMAX module that can
    affect the simulation results and reported to
    NS-3 community at http//www.nsnam.org/bugzilla/s
    how_bug.cgi?id1025
  • Simulation Experiments in NS-3
  • The initialization phase of wireless networks
  • Bugs in Wi-Fi Mesh, WiMAX modules

26
Future Direction
  • Fully integrate the SG-WIP tool with SG-SIM
    simulator
  • Improve the antenna placement algorithm
  • Increase availability of wireless networks
  • Database systems for storing the real-time meter
    data

27
Conclusion
  • The proposed WiMAX/Wi-Fi WMN can transport the
    meter data from 160,000 smart meters in the CSU
    service areas to the data center in one second.
  • The high scalability property of WiMAX/Wi-Fi WMN
    helps flexibly extend the coverage area of the
    AMI wireless infrastructure without degrading the
    network performance.
  • The proposed WiMAX/Wi-Fi infrastructure allows
    the utilities deploying an AMI wireless
    communication infrastructure not only at low cost
    of installation and maintenance but also with
    high performance, scalability, and security.

28
Demo
  • Illustrate network topology planning with SG-WIP
    Tool
  • http//scad.eas.uccs.edu/sgwip/wan.html
  • Some demonstrations of SG-SIM simulator

29
References
  • DoE01 U.S. Department of Energy, Smart Grid,
    lthttp//www.oe.energy.gov/smartgrid.htmgt
  • DoE02 U.S Department of Energy, Smart Grid An
    Introduction, lthttp//www.oe.energy.gov/SmartGrid
    Introduction.htmgt
  • Wiki01 Smart Grid, lthttp//en.wikipedia.org/wi
    ki/Smart_gridgt
  • NIST10 National Institute of Standards and
    Technology, NIST Framework and Roadmap for Smart
    Grid Interoperability Standards, Release 1.0,
    Jan. 2010.
  • NETL08 National Energy Technology Laboratory,
    white paper Advanced Metering infrastructure,
    February 2008.
  • Chow09 Edward Chow, Lecture Secure Smart
    Grids, Department of Computer Science,
    University of Colorado at Colorado Springs, 2009.
  • IEEE11 IEEE Standard 802 Part 11 Wireless LAN
    Medium Access Control (MAC) and Physical Layer
    (PHY) Specifications, 2007.
  • IEEE15 IEEE Standard 802 Part 15.1 Wireless
    Medium Access Control (MAC) and Physical Layer
    (PHY) Specifications for Personal Area Networks
    (WPANs), 2005.
  • IEEE16 IEEE Standard 802 Part 16 Air Interface
    for Broadband Wireless Access Systems, 2009.
  • IEEE11s IEEE, Draft amendment ESS mesh
    networking, IEEE P802.11s Draft 1.00, November
    2006.
  • Moh01 Prasant Mohapatra, Lecture Wireless Mesh
    Networks, Department of Computer Science
    University of California, Davis.
  • AWW05 I. F. Akyildiz, X. Wang, and W. Wang,
    "Wireless Mesh Networks A Survey," Computer
    Networks Journal (Elsevier), vol. 47, no. 4, pp.
    445-487, Mar. 2005.
  • Kri01 Srini Krishnamurthy, Smart AMI Network
    Solutions Enable the Smart Grid,
    ElectricEnergyOnline.com, lthttp//www.electricener
    gyonline.com/?pageshow_articlemag55article395
    gt
  • Met01 MetroFi, lthttp//en.wikipedia.org/wiki/Me
    troFigt
  • Sky01 SkyPilot, lthttp//skypilot.trilliantinc.co
    mgt
  • Eka01 EkaNet, lthttp//www.ekasystems.com/ekanet.
    htmgt
  • JS03 J. Jangeun and M. L. Sichitiu, The
    Nominal Capacity of Wireless Mesh Networks, in
    IEEE Wireless Communications Magazine, October
    2003, vol. 10 no. 5, pp. 814.
  • RC05 A. Raniwala and T. cker Chiueh,
    Architecture and Algorithms for an IEEE
    802.11-based Multi-channel Wireless Mesh
    Network, in Proceedings of INFOCOM 2005, March
    2005, vol. 3, pp. 22232234.
  • ANMK08 Akhtar, Nadeem and Moessner, Klaus,
    Capacity of Grid-Oriented Wireless Mesh
    Networks, 3rd International Conference on
    Communication Systems Software and Middleware and
    Workshops, Volumes 1 and 2 . pp. 631-636.
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