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Design and Performance Evaluation of Cognitive Radio for Real-Time Communication in Smart Grid

Dehalwar, Vasudev (2017) Design and Performance Evaluation of Cognitive Radio for Real-Time Communication in Smart Grid. PhD thesis, Victoria University.

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Abstract

The electric power grid has been developed over the last century which lacks bi-directional flow of data. The advancement in Information and Communication Technology (ICT) has motivated to convert the existing grid into the Smart Grid. The Sensors, Intelligent Electronic Devices (IEDs), Phasor Measurement Unit (PMU), etc. are the backbone of Smart Grid network. The billions of installed components in Smart Grid will generate high volumes of operation and control data. Transferring this high-volume data in the Smart Grid network is a big challenge! The present communication technology has limitations in delivering the Big Data of Smart Grid to control center in real-time. This research explores the possibility of using IEEE802.22 international standard for communication of Big Data. IEEE802.22 uses Cognitive Radio for communication that allows opportunistic use of unused TV white space by Secondary User if that spectrum is not being used by Primary User. This study reflects on following the points: *(i) The prospects of Integrating IEC61850 with IEEE802.22; *(ii) Probability of sensing Primary User’s spectrum efficiently in real-time for optimum use of spectrum in Cognitive Radio; and *(iii) Verifying the feasibility of Cognitive Radio to meet the timing constraints (latency) of data transmission for power protection.

Item Type: Thesis (PhD thesis)
Uncontrolled Keywords: smart grid, cognitive radio, machine to machine communication, M2M, spectrum sensing, advance metering infrastructure, AMI, teleprotection, IEEE802.22, wireless regional area network, WRAN, big data, field area network, FAN, IEC61850, load forecasting, NS-2, NS-3
Subjects: FOR Classification > 1005 Communications Technologies
Faculty/School/Research Centre/Department > College of Science and Engineering
Depositing User: VU Library
Date Deposited: 02 Oct 2017 04:39
Last Modified: 02 Oct 2017 04:39
URI: http://vuir.vu.edu.au/id/eprint/34717
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