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Experimental Verification and Integr...

Clemmer, Tavis B.

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Experimental Verification and Integration of a Next Generation Smart Power Management System.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Experimental Verification and Integration of a Next Generation Smart Power Management System./
Author:	Clemmer, Tavis B.
Description:	238 p.
Notes:	Source: Masters Abstracts International, Volume: 54-04.
Contained By:	Masters Abstracts International54-04(E).
Subject:	Alternative Energy. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1586426
ISBN:	9781321680225

Experimental Verification and Integration of a Next Generation Smart Power Management System.
Clemmer, Tavis B.

Experimental Verification and Integration of a Next Generation Smart Power Management System. - 238 p.

Source: Masters Abstracts International, Volume: 54-04.

Thesis (M.S.E.E.)--University of Arkansas, 2015.

With the increase in energy demand by the residential community in this country and the diminishing fossil fuel resources being used for electric energy production there is a need for a system to efficiently manage power within a residence. The Smart Green Power Node (SGPN) is a next generation energy management system that automates on-site energy production, storage, consumption, and grid usage to yield the most savings for both the utility and the consumer. Such a system automatically manages on-site distributed generation sources such as a PhotoVoltaic (PV) input and battery storage to curtail grid energy usage when the price is high. The SGPN high level control features an advanced modular algorithm that incorporates weather data for projected PV generation, battery health monitoring algorithms, user preferences for load prioritization within the home in case of an outage, Time of Use (ToU) grid power pricing, and status of on-site resources to intelligently schedule and manage power flow between the grid, loads, and the on-site resources.

ISBN: 9781321680225Subjects--Topical Terms:

1035473
Alternative Energy.

Experimental Verification and Integration of a Next Generation Smart Power Management System.
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245 1 0 $a Experimental Verification and Integration of a Next Generation Smart Power Management System.
300 $a 238 p.
500 $a Source: Masters Abstracts International, Volume: 54-04.
500 $a Adviser: Dr. Alan Mantooth.
502 $a Thesis (M.S.E.E.)--University of Arkansas, 2015.
520 $a With the increase in energy demand by the residential community in this country and the diminishing fossil fuel resources being used for electric energy production there is a need for a system to efficiently manage power within a residence. The Smart Green Power Node (SGPN) is a next generation energy management system that automates on-site energy production, storage, consumption, and grid usage to yield the most savings for both the utility and the consumer. Such a system automatically manages on-site distributed generation sources such as a PhotoVoltaic (PV) input and battery storage to curtail grid energy usage when the price is high. The SGPN high level control features an advanced modular algorithm that incorporates weather data for projected PV generation, battery health monitoring algorithms, user preferences for load prioritization within the home in case of an outage, Time of Use (ToU) grid power pricing, and status of on-site resources to intelligently schedule and manage power flow between the grid, loads, and the on-site resources.
520 $a The SGPN has a scalable, modular architecture such that it can be customized for user specific applications. This drove the topology for the SGPN which connects on-site resources at a low voltage DC microbus; a two stage bi-directional inverter/rectifier then couples the AC load and residential grid connect to on-site generation. The SGPN has been designed, built, and is undergoing testing. Hardware test results obtained are consistent with the design goals set and indicate that the SGPN is a viable system with recommended changes and future work.
590 $a School code: 0011.
650 4 $a Alternative Energy. $3 1035473
650 4 $a Electrical engineering. $3 649834
650 4 $a Energy. $3 876794
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710 2 $a University of Arkansas. $b Electrical Engineering. $3 2103922
773 0 $t Masters Abstracts International $g 54-04(E).
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