Hardware Testing of Electric Hot Water Heaters Providing Energy Storage and Demand Response Through Model Predictive Control

This paper presents results from hardware testing which demonstrate that, 1) systems of water heaters under Model Predictive Control can be reliably dispatched to deliver set-point levels of power to within 2% error at very short timescales with minimal sensing requirements, and 2) a classical stead...

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Main Authors: Douglas A. Halamay, Mike Starrett, Ted K. A. Brekken
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8798994/
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spelling doaj-c485e154203f4504a1b1cd925751b51c2021-03-29T23:13:26ZengIEEEIEEE Access2169-35362019-01-01713904713905710.1109/ACCESS.2019.29329788798994Hardware Testing of Electric Hot Water Heaters Providing Energy Storage and Demand Response Through Model Predictive ControlDouglas A. Halamay0Mike Starrett1https://orcid.org/0000-0002-1977-057XTed K. A. Brekken2Eaton Corporation, Portland, OR, USANorthwest Power and Conservation Council, Portland, OR, USASchool of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, USAThis paper presents results from hardware testing which demonstrate that, 1) systems of water heaters under Model Predictive Control can be reliably dispatched to deliver set-point levels of power to within 2% error at very short timescales with minimal sensing requirements, and 2) a classical steady state model commonly used for simulation of electric hot water heaters can be inaccurate vs. results obtained on hardware. These results improve upon the current state of knowledge and show a promising pathway to control hot water heaters as energy storage systems capable of delivering flexible capacity and fast acting ancillary services on a firm basis. These energy products are shown to be deliverable without compromising the availability of hot water at the residence, even in control implementations which do not have sensors to monitor actual water use for the predictive optimization.https://ieeexplore.ieee.org/document/8798994/Demand responseenergy storagemodel predictive controlwater heating
collection DOAJ
language English
format Article
sources DOAJ
author Douglas A. Halamay
Mike Starrett
Ted K. A. Brekken
spellingShingle Douglas A. Halamay
Mike Starrett
Ted K. A. Brekken
Hardware Testing of Electric Hot Water Heaters Providing Energy Storage and Demand Response Through Model Predictive Control
IEEE Access
Demand response
energy storage
model predictive control
water heating
author_facet Douglas A. Halamay
Mike Starrett
Ted K. A. Brekken
author_sort Douglas A. Halamay
title Hardware Testing of Electric Hot Water Heaters Providing Energy Storage and Demand Response Through Model Predictive Control
title_short Hardware Testing of Electric Hot Water Heaters Providing Energy Storage and Demand Response Through Model Predictive Control
title_full Hardware Testing of Electric Hot Water Heaters Providing Energy Storage and Demand Response Through Model Predictive Control
title_fullStr Hardware Testing of Electric Hot Water Heaters Providing Energy Storage and Demand Response Through Model Predictive Control
title_full_unstemmed Hardware Testing of Electric Hot Water Heaters Providing Energy Storage and Demand Response Through Model Predictive Control
title_sort hardware testing of electric hot water heaters providing energy storage and demand response through model predictive control
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description This paper presents results from hardware testing which demonstrate that, 1) systems of water heaters under Model Predictive Control can be reliably dispatched to deliver set-point levels of power to within 2% error at very short timescales with minimal sensing requirements, and 2) a classical steady state model commonly used for simulation of electric hot water heaters can be inaccurate vs. results obtained on hardware. These results improve upon the current state of knowledge and show a promising pathway to control hot water heaters as energy storage systems capable of delivering flexible capacity and fast acting ancillary services on a firm basis. These energy products are shown to be deliverable without compromising the availability of hot water at the residence, even in control implementations which do not have sensors to monitor actual water use for the predictive optimization.
topic Demand response
energy storage
model predictive control
water heating
url https://ieeexplore.ieee.org/document/8798994/
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AT tedkabrekken hardwaretestingofelectrichotwaterheatersprovidingenergystorageanddemandresponsethroughmodelpredictivecontrol
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