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Intelligent MicroGrid Communication Networks

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  1. Intelligent MicroGrid Communication Networks Theme 3, Project 3.2 Tho Le-Ngoc (McGill University) Quang-Dung Ho (Research Associate) Gowdemy Rajalingham (MEng Student) Chon-Wang Chao (MEng Student) Yue Gao (MEng Student)

  2. Summary NSMG-Net Project 3.2: Gowdemy Rajalingham

  3. Proposed System Architecture & Evaluation Fig. 1 – Neighbor Area Network • Objective • Determine capabilities and limitations of NAN with GPSR • Investigate NAN clusters performance with various system parameters Fig. 2 – Simulation Scenario, sweep of cluster size NSMG-Net Project 3.2: Gowdemy Rajalingham

  4. Feasibility of Candidate Routing for Nan • Performance Versus Cluster Size and Data Rate Current Estimates • Base Rate: NIST Data Rate of 0.00195 pps (based on simple meter readings) • Typical AMI deployment NAN size: A few 1000s of smart meters Results • Can maintain latency < 100 ms for up to 6000 nodes for data rates up to 10x base data rate • Can maintain PDR > 95% for up to 6000 nodes for data rates up to 10x base data rate • At 100x base data rate, to maintain latency < 100 ms and PDR > 95%, cannot exceed a cluster size of roughly 1500 NSMG-Net Project 3.2: Gowdemy Rajalingham Fig. 4 –, Packet Delivery ratio vs. Cluster size Fig. 3 –, 95% Percentile of delay vs. Cluster size

  5. Publications • [1] Quang-Dung Ho, Gao Yue and Tho Le-Ngoc, “Challenges and Research Opportunities in Wireless Communication Networks for Smart Grid”, IEEE Wireless Communications Magazine, June 2013. • [2] Chon-Wang Chao, Quang-Dung Ho and Tho Le-Ngoc, ”Challenges of Power Line Communications for Advanced Distribution Automation in Smart Grid”, 2013 IEEE Power and Energy Society General Meeting, Vancouver-Canada, July 21-25 2013. • [3] Gowdemy Rajalingham, Quang-Dung Ho and Tho Le-Ngoc, “Attainable Throughput, Delay and Scalability for Geographic Routing on Smart Grid Neighbor Area Networks”, 2013 IEEE Wireless Communications and Networking Conference (WCNC 2013), Shanghai-China, 7-10 April 2013. • [4] Gowdemy Rajalingham and Quang-Dung Ho, “LTE HetNets: Challenges and Opportunities for Integration of Smart Grid Networks”, Technical Report, McGill, April 2013. • [5] Chon-Wang Chao and Quang-Dung Ho, “Communication Standard and Network Infrastructure Considerations for Smart Grid”, Technical Report, McGill, 2012. • [6]Yue Gao and Quang-Dung Ho, “OMNET Implementation of RPL for Smart Grid Neighbor Area Networks”, Technical Report, McGill, December 2012. NSMG-Net Project 3.2: Gowdemy Rajalingham

  6. BACKUP SLIDES

  7. Introduction • Objective • Project 3.2 aims to study and to develop relevant transmission, information processing, and networking techniques for an efficient and reliable IMG Communication Network (IMGCN) • Issues • The successful implementation of the Intelligent MicroGrids (IMGs) requires an efficient communications infrastructurethat is cost-effective, scalable, fault-tolerant, secure& satisfies the QoSrequirements (data rate, delay, reliability) Fig. x – Full Abstract System Architecture Model NSMG-Net Project 3.2: Gowdemy Rajalingham

  8. Applicability of PLC

  9. Applicability of Power-Line Communications • Key Contributions • Calculated the expected data rate requirements with IEC 61850 message architecture and power network parameters • Examined the impacts of channel competition with Carrier Sense Multi-Access/Collision Avoidance (CSMA/CA) algorithm on saturation throughput (T) and bandwidth requirement • Further details in poster “Throughput Analysis of Narrowband PLC in Advanced Distribution Automation” Fig. x – Communication PLC Network NSMG-Net Project 3.2: Gowdemy Rajalingham

  10. Applicability of Power-Line Communications • Summary of Results • Expected data rate with only PLC supporting advanced distribution automation is 310.69 kbps • Throughput and bandwidth requirement variation • T decreases as the number of nodes increases (higher probability of collision) • The optional Request to Send/Clear to Send mechanism can increase the T with same number of nodes and reduce to growth rate of bandwidth requirement • Existing field tested PLC technology may not be able to provide enough data rate • Further details in poster “Throughput Analysis of Narrowband PLC in Advanced Distribution Automation” Fig. x – Communication PLC Network NSMG-Net Project 3.2: Gowdemy Rajalingham

  11. Frequency Regulation Using EV Charging Control

  12. Frequency Regulation Using EV Charging Control • Key Contributions • Proposed a new aggregator based electric vehicle charging control scheme with priority indices • Proposed to use the joint simulation platform to study the effects of communication delays and packet loss • Further details in poster “Cost-Effective Frequency Regulation by Aggregator-based EV Charging Control via Wireless Communications” Fig. x – Proposed Control Structure and Neighborhood Mapping NSMG-Net Project 3.2: Gowdemy Rajalingham

  13. Frequency Regulation Using EV Charging Control • Control System Model • Further details in poster “Cost-Effective Frequency Regulation by Aggregator-based EV Charging Control via Wireless Communications” Fig. x – Proposed Control Block Diagram and Joint Simulation Setup NSMG-Net Project 3.2: Gowdemy Rajalingham

  14. Frequency Regulation Using EV Charging Control • Communications Model • Further details in poster “Cost-Effective Frequency Regulation by Aggregator-based EV Charging Control via Wireless Communications” Fig. x – EV Selection Algorithm NSMG-Net Project 3.2: Gowdemy Rajalingham

  15. Frequency Regulation Using EV Charging Control • Illustrative Example • Further details in poster “Cost-Effective Frequency Regulation by Aggregator-based EV Charging Control via Wireless Communications” Fig. x – Illustrative Example NSMG-Net Project 3.2: Gowdemy Rajalingham Number of EV = 120 Ithreshold = 98

  16. Proposed Architecture

  17. Survey of Technologies • Wired Technologies • Economically feasible when network cables and related facilities are pre-existing and readily available at acceptable low costs • More suitable for back-haul links for large volume of traffic • Example: Digital subscriber line (DSL), leased line, power line communications (PLC), fiber optics … Wireless Technologies Home Area Network • 10-100 kbps • Coverage area of up to 100 m2 • Example: ZigBee, WirelessHART, 6LowPan, Bluetooth, … Neighbor Area Network • 10-100 kbps • Coverage area of up to several km2 • Example: Wi-Fi, Wi-Fi Mesh, … Wide Area Network • 10-100 Mbps • Coverage area of up to several 100 km2 • Example: WiMax, LTE, … Fig. x – Potential Technologies NSMG-Net Project 3.2: Gowdemy Rajalingham

  18. Candidate Wireless Architectures Fig. X – Potential NAN/WAN Interconnections LEGEND: Excellent, Adequate, Deficient NSMG-Net Project 3.2: Gowdemy Rajalingham

  19. Proposed System Architecture Fig. X – Potential NAN/WAN Interconnections Fig. X – Proposed NAN/WAN Interconnections Fig. x – Neighbor Area Network NSMG-Net Project 3.2: Gowdemy Rajalingham

  20. Neighbor Area Network

  21. Neighbor Area Network Fig. x – Potential Technologies Fig. x – Full Abstract System Architecture Model • Network Characteristics • Network of smart meters, repeaters, collectors • Static, line powered, heterogeneous multi-tiered network • Communications protocols must be robust, scalable, self-configurable and self-healing • Traffic Characteristics • Multiple-Point-to-Point • Point-to-Multiple-Point • Point-to-Point • Large volume of devices • Short bursty packets • Quality of Service (QoS) differentiation • Mix of real-time ( < 10 ms) and non-real-time traffic (seconds - min) Fig. x – Neighbor Area Network NSMG-Net Project 3.2: Gowdemy Rajalingham

  22. Neighbor Area Network Fig. x – Neighbor Area Network • Network Characteristics • Network of smart meters, repeaters, collectors • Static, line powered, heterogeneous multi-tiered network • Communications protocols must be robust, scalable, self-configurable and self-healing • Traffic Characteristics • Multi-point-to-point, point-to-multi-point, point-to-point • Large volume of devices with short bursty packets • Quality of Service (QoS) differentiation • Real-time (<10ms) & non-real-time traffic (sec/min) NSMG-Net Project 3.2: Gowdemy Rajalingham

  23. Feasibility of Candidate Routing for Nan • Objective • Determine the capabilities and limitations of NAN • With respect to ability to host MicroGrid applications • With GPSR routing protocol • Thus, performance of NAN clusters with various system parameters is investigated • Expected Results • As channel conditions worsen, performance degrades due to more likely packet corruption and retransmissions • As data rate increases, higher chance for channel contention, back-offs and packet retransmissions lead to increased delay and reduced reliability • As cluster size increases, • Increase in network load and average hop count • Significant increase in network delay with decreasing PDR Fig. x – Simulation Scenario, sweep of cluster size NSMG-Net Project 3.2: Gowdemy Rajalingham