Date of Award:

5-2016

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Electrical and Computer Engineering

Committee Chair(s)

Jacob H. Gunther

Committee

Jacob H. Gunther

Committee

Don Cripps

Committee

Bedri Cetiner

Abstract

The gathered data from smart meters in current advanced metering infrastructure (AMI) of smart grid is huge. This much data causes serious challenges for reliability, performance, and scalability of smart grid. Therefore, we have investigated the scalability of different AMI architectures and proposed a scalable hybrid AMI architecture. We formulated deployment cost of different AMI architecture and used a genetic-based algorithm to minimize the deployment cost for the proposed architecture. We simulated different AMI architectures for five demographic regions and the results proved that our proposed AMI hybrid architecture has a better scalability compared to other AMI architectures.

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