Synchronization and Rebound Effects in Residential Loads

Increasing fuel prices and capacity investment deferral place an increasing demand for peak reduction from distribution level systems. Residential and commercial devices, such as HVAC systems and water heaters, are increasingly involved in load control programs, and their use may generate synchroniz...

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Main Authors: Nora Agah, Eve Tsybina, Viswadeep Lebakula, Justin Hill, Jeff Munk, Helia Zandi
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Open Access Journal of Power and Energy
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10606292/
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author Nora Agah
Eve Tsybina
Viswadeep Lebakula
Justin Hill
Jeff Munk
Helia Zandi
author_facet Nora Agah
Eve Tsybina
Viswadeep Lebakula
Justin Hill
Jeff Munk
Helia Zandi
author_sort Nora Agah
collection DOAJ
description Increasing fuel prices and capacity investment deferral place an increasing demand for peak reduction from distribution level systems. Residential and commercial devices, such as HVAC systems and water heaters, are increasingly involved in load control programs, and their use may generate synchronization and rebound effects, such as artificial peaks caused by device optimization. While there have been concerns over device synchronization, few studies quantify the extent of this effect with numerical values. In this study, we attempt to investigate whether control efforts result in device synchronization or rebound effects. We focus on three clustering methods – Ward’s clustering, Euclidean K-means, and Density-based spatial clustering of applications with noise – to evaluate the extent of synchronization of a fleet of water heaters and HVAC systems in Atlanta, Georgia. Our findings show that synchronization and rebound effects are present in the neighborhood’s water heaters, but none were found in the HVAC systems. Further, high usage water heaters are more susceptible to synchronization and rebound effects.
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institution Kabale University
issn 2687-7910
language English
publishDate 2024-01-01
publisher IEEE
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series IEEE Open Access Journal of Power and Energy
spelling doaj-art-2082a31a351743f3ae426a88d0aa4ebf2025-01-21T00:03:11ZengIEEEIEEE Open Access Journal of Power and Energy2687-79102024-01-011167668910.1109/OAJPE.2024.343238910606292Synchronization and Rebound Effects in Residential LoadsNora Agah0https://orcid.org/0000-0003-0271-1204Eve Tsybina1https://orcid.org/0000-0001-8131-1828Viswadeep Lebakula2https://orcid.org/0000-0001-5293-5914Justin Hill3https://orcid.org/0000-0003-3329-3367Jeff Munk4Helia Zandi5https://orcid.org/0000-0003-3966-7454Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USAOak Ridge National Laboratory, Oak Ridge, TN, USAOak Ridge National Laboratory, Oak Ridge, TN, USASouthern Company, Birmingham, AL, USANational Renewable Energy Laboratory, Golden, CO, USAOak Ridge National Laboratory, Oak Ridge, TN, USAIncreasing fuel prices and capacity investment deferral place an increasing demand for peak reduction from distribution level systems. Residential and commercial devices, such as HVAC systems and water heaters, are increasingly involved in load control programs, and their use may generate synchronization and rebound effects, such as artificial peaks caused by device optimization. While there have been concerns over device synchronization, few studies quantify the extent of this effect with numerical values. In this study, we attempt to investigate whether control efforts result in device synchronization or rebound effects. We focus on three clustering methods – Ward’s clustering, Euclidean K-means, and Density-based spatial clustering of applications with noise – to evaluate the extent of synchronization of a fleet of water heaters and HVAC systems in Atlanta, Georgia. Our findings show that synchronization and rebound effects are present in the neighborhood’s water heaters, but none were found in the HVAC systems. Further, high usage water heaters are more susceptible to synchronization and rebound effects.https://ieeexplore.ieee.org/document/10606292/Demand responsedirect load controlpeak shiftingwater heaterHVACsynchronization
spellingShingle Nora Agah
Eve Tsybina
Viswadeep Lebakula
Justin Hill
Jeff Munk
Helia Zandi
Synchronization and Rebound Effects in Residential Loads
IEEE Open Access Journal of Power and Energy
Demand response
direct load control
peak shifting
water heater
HVAC
synchronization
title Synchronization and Rebound Effects in Residential Loads
title_full Synchronization and Rebound Effects in Residential Loads
title_fullStr Synchronization and Rebound Effects in Residential Loads
title_full_unstemmed Synchronization and Rebound Effects in Residential Loads
title_short Synchronization and Rebound Effects in Residential Loads
title_sort synchronization and rebound effects in residential loads
topic Demand response
direct load control
peak shifting
water heater
HVAC
synchronization
url https://ieeexplore.ieee.org/document/10606292/
work_keys_str_mv AT noraagah synchronizationandreboundeffectsinresidentialloads
AT evetsybina synchronizationandreboundeffectsinresidentialloads
AT viswadeeplebakula synchronizationandreboundeffectsinresidentialloads
AT justinhill synchronizationandreboundeffectsinresidentialloads
AT jeffmunk synchronizationandreboundeffectsinresidentialloads
AT heliazandi synchronizationandreboundeffectsinresidentialloads