Presentation of Master’s thesis Simulation and Analysis of Wireless Mesh Network In Smart Grid / Advanced Metering Infrastructure Philip Huynh

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 SGSim Lesson Learned Future Direction Conclusion

Introduction What is smart grid? Smart grid conceptual framework

Introduction cont. The need to collect metering data in real-time Save the material usage to generate the electric power by correctly predict the load demand and build the load profile Meter Data Warehousing

Research opportunity & Goals Academic researches provides the nominal evaluation of the performance of WMN. For example: Commercial products in the smart grid field has not supported the real-time metering data collection. An important issue causes low performance in their WMN is the network architecture. Research Opportunities WMN architecture: high performance, low cost Methodology for evaluating the performance of WMN in real-time metering data collection Goals Develop techniques and tools to evaluate the performance of WMN in smart grid / AMI

CSU AMI Infrastructure

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. “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.

Related Work cont. “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. “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 “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.

Related Work cont. “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.

HW2N for SG Meter Data Collection Example of WAN topology (WiMAX) Example of NAN topology (Wi-Fi) Hybrid WiMAX/Wi-Fi Network Model

SG-WIP Planning Tool Visually planning the Antenna mounting place for the WiMAX/Wi-Fi WMN This is a mashup that overlays the Wireless Infrastructure, GIS data (street light poles, housing units) using the Google Maps. Export the network topology as file for further research Can be integrated to the network simulator

SG-WIP Tool

SG-WIP Tool cont. WAN Grid 10x10 Topology, 10 km x 10 km (WxH) NAN Grid 10x10 Topology, 1 km x 1 km (WxH)

SG-WIP Tool cont. LAN Square Topology, 100 m x 100 m (WxH) Topology is exported as XML file

SG-WIP Tool cont. Before changing the WiMAX antennae After changing the WiMAX antennae

SG-WIP Tool cont. Google Maps mashup code

SG-SIM Simulator Implement the proposed hybrid WiMAX/Wi-Fi Network Model in NS-3 Platform Tools used (created by others…; give credits to them) Parameters of the Simulator Network types: WAN, MAN, NAN, LAN Number of nodes, Transmission Rate Others: network initialization time,…

SG-SIM Simulator cont. NS-3 simulator code

Simulation Experiments Experiment Design Vision Evaluate the performance of AMI Infrastructure Trade-off between Scalability and Performance Confirm to smart meter density analysis (using SG-WIP)

LAN Simulation Results Tx packets = Rx packets = 50 (each sec) Delay time converges to 10 msecs Total processing delay converges to 10 msecs Tx packets = Rx packets Total processing delay increases linearly with the number of smart meter

NAN Simulation Results Tx packets = Rx packets = 450 (each sec) Delay time converges to 200 usecs Total processing delay converges to 10 msecs Tx packets = Rx packets Total processing delay increases rapidly with the number of mesh routers

MAN Simulation Results Tx packets = 1,800 (each sec) Rx packets = Tx ± 5 (each sec) Delay time converges to 5.5 msecs Total processing delay converges to 930 msecs Tx packets = Rx packets Total processing delay is in narrow range [930, 960] msecs. It confirms to 5 msecs fixed frame time in 802.16 std.

MAN Simulation Results cont. Impact On The Network Performance By Aggregating Meter Data Impact On The Network Performance By Aggregating Meter Data MAN Simulation Results cont. Impact on the network performance by aggregating meter data at the gateway Tx packets = Rx packets when number of meter data packets < 16 Tx packets > Rx packets when number of meter data packets >= 16 (overloaded) Total processing delay increases linearly with the number of meter packets

WAN Simulation Results

WAN Simulation Results cont.

Google Maps service + GIS infrastructure information Lessons Learned A useful mashup for visual planning AMI infrastructure Google Maps service + GIS infrastructure information 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/show_bug.cgi?id=1025 Simulation Experiments in NS-3 The initialization phase of wireless networks

Future work 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

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.

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

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