Electrical & Computer Engineering: Faculty Publications

PicoGrid Smart Home Energy Management System

Document Type

Conference Proceeding

Publication Date

10-4-2018

Publication Title

Southeastcon 2018 Proceedings

DOI

10.1109/SECON.2018.8479129

Abstract

Due to increased automation in the home, the needed capacity of electrical distribution grids is continuously growing larger to accommodate peak usage, leading to underutilized capacity during nonpeak usage hours. To assist homeowners in identifying large electrical loads and wasted energy usage in the home environment, this paper proposes a novel method of measuring power usage and automatically identifying and classifying the device through the use of an artificial neural network. The result would be a method of reviewing energy usage per device connected to the picogrid over a defined interval regardless of which monitored outlet the device is connected to for utility power. The neural network classifier further provides the ability to track appliance performance over time and compare changes in power draw. Prototype testing of the proposed system has yielded promising results in both the ability to measure consumed power and to classify devices when connected to the metered outlet.

Comments

Georgia Southern University faculty member, Rami J. Haddad co-authored, "PicoGrid Smart Home Energy Management System."

Copyright

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