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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Online Access: | https://ieeexplore.ieee.org/document/8798994/ |
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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/ |
work_keys_str_mv |
AT douglasahalamay hardwaretestingofelectrichotwaterheatersprovidingenergystorageanddemandresponsethroughmodelpredictivecontrol AT mikestarrett hardwaretestingofelectrichotwaterheatersprovidingenergystorageanddemandresponsethroughmodelpredictivecontrol AT tedkabrekken hardwaretestingofelectrichotwaterheatersprovidingenergystorageanddemandresponsethroughmodelpredictivecontrol |
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1724189918650957824 |