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Device to Device Communications for Smart Grid

This thesis identifies and addresses two barriers to the adoption of Long Term Evolution (LTE) Device-to-Device (D2D) communication enabled smart grid applications in out of core network coverage regions. The first barrier is the lack of accessible simulation software for engineers to develop and test the feasibility of their D2D LTE enabled smart grid application designs. The second barrier is the lack of a distributed resource allocation algorithm for LTE D2D communications that has been tailored to the needs of smart grid applications.
A solution was proposed to the first barrier in the form of a simulator constructed in
Matlab/Simulink used to simulate power systems and the underlying communication
system, i.e., D2D communication protocol stack of Long Term Evolution (LTE). The
simulator is built using Matlab's LTE System Toolbox, SimEvents, and Simscape Power Systems in addition to an in-house developed interface software to facilitate D2D communications in smart grid applications. To test the simulator, a simple fault location, isolation, and restoration (FLISR) application was implemented using the simulator to show that the LTE message timing is consistent with the relay signaling in the power system.
A solution was proposed to the second barrier in the form of a multi-agent Q-learning based resource allocation algorithm that allows Long Term Evolution (LTE) enabled
device-to-device (D2D) communication agents to generate orthogonal transmission schedules outside of network coverage. This algorithm reduces packet drop rates (PDR) in distributed D2D communication networks to meet the quality of service requirements of microgrid communications. The PDR and latency performance of the proposed algorithm was compared to the existing random self-allocation mechanism introduced under the Third Generation Partnership Project's LTE Release 12. The proposed algorithm outperformed the LTE algorithm for all tested scenarios, demonstrating 20-40% absolute reductions in PDR and 10-20 ms reductions in latency for all microgrid applications.

Identiferoai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/40656
Date17 June 2020
CreatorsShimotakahara, Kevin
ContributorsErol Kantarci, Melike, Hinzer, Karin
PublisherUniversité d'Ottawa / University of Ottawa
Source SetsUniversité d’Ottawa
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf

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