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Communication System Design for an Advanced Metering Infrastructure.
Ricardo Siqueira de Carvalho1, Pankaj Kumar Sen2, Yaswanth Nag Velaga3
1Department of Electrical Engineering, Colorado School of Mines, Golden CO 80401, USA. rsiqueiradecarvalho@mines.edu.
Sensors (Basel, Switzerland)
|November 8, 2018
Summary
This study designs an Information and Control Technology (ICT) network for advanced metering infrastructure (AMI) using power line carrier (PLC) communication. Simulation results validate the network
Area of Science:
- Electrical Engineering
- Computer Networking
- Smart Grid Technology
Background:
- Advanced Metering Infrastructure (AMI) requires robust Information and Control Technology (ICT) networks.
- The IEEE 34 node radial distribution network serves as a testbed for smart grid applications.
- Power Line Carrier (PLC) communication is a viable option for AMI data transmission.
Purpose of the Study:
- To design and simulate an ICT network for AMI on the IEEE 34 node radial distribution network.
- To evaluate the performance of a PLC communication system for smart meters and data concentrators.
- To assess AMI's potential as a source of big data in future power grids.
Main Methods:
- Design of an ICT network integrating 330 smart meters and 33 data concentrators.
- Simulation of a Power Line Carrier (PLC) communication system using Network Simulator 3 (NS-3).
- Validation of simulation results against minimum AMI performance requirements and calculation of network delay.
Main Results:
- The designed PLC communication system meets the minimum performance requirements for AMI.
- Network delay calculations align with simulation outcomes, confirming system viability.
- Analysis of AMI network traffic based on IEC Std. 61968 standards.
Conclusions:
- The proposed ICT network design is suitable for AMI and potentially other smart grid applications.
- The PLC communication system demonstrates effective performance for smart metering data.
- Advanced Metering Infrastructure (AMI) is identified as a significant potential source of big data for future power grids.
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