2015
DOI: 10.2172/1177305
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Evaluation of the Demand Response Performance of Electric Water Heaters

Abstract: The team also wishes to acknowledge Dennis Stiles and Rob Pratt for their management support; Jason Fuller, Andrew Fisher, Laurentiu Marinovici for their technical assistance running GridLAB-D simulations; Dave Winiarski for his technical insights and guidance; and Marye Hefty who assisted in the project planning and analysis of industry comments. v

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Cited by 12 publications
(11 citation statements)
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“…For more information, visit: energy.gov/eere/buildings/grid-interactive-efficient-buildings. (Denholm et al 2019;CAISO 2018b) Variablefrequency drives (Macdonald et al 2014), water heaters (Hledik et al 2016;Mayhorn et al 2015) Delivery Services Moderate. Opportunities to defer or avoid the need for investments in T&D infrastructure are highly location dependent.…”
Section: Field Validation and Implementationmentioning
confidence: 99%
“…For more information, visit: energy.gov/eere/buildings/grid-interactive-efficient-buildings. (Denholm et al 2019;CAISO 2018b) Variablefrequency drives (Macdonald et al 2014), water heaters (Hledik et al 2016;Mayhorn et al 2015) Delivery Services Moderate. Opportunities to defer or avoid the need for investments in T&D infrastructure are highly location dependent.…”
Section: Field Validation and Implementationmentioning
confidence: 99%
“…For more information, visit: energy.gov/eere/buildings/grid-interactive-efficient-buildings. 26 Range based on observed differences between average peak and off-peak prices reported for ERCOT ($8.41/MWh; Potomac Economics 2018a), ISO-NE ($7.30/MWh; ISO-NE 2018b), and CAISO ($50-$60/MWh; Hildebrandt et al 2018 (Macdonald et al 2014), water heaters (Hledik et al 2016;Mayhorn et al 2015) Delivery Services Non-Wires Solutions $0-$200 per kW reduction in peak downstream demand per year (Baatz 2015) Location and utility dependent. Based on a survey of utility companies.…”
Section: Field Validation and Implementationmentioning
confidence: 99%
“…The load control law was designed in a hierarchically decentralized manner consisting of two interactive decision layers. In the first layer, a supervisory controller is responsible to gather system-level information (e.g., power flow, system topology, generation and load forecast, available responsive loads, among others), and determine the optimal gains for the responsive loads on each bus every few (e.g., [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] minutes. In the second layer, each decentralized load switched ON/OFF probabilistically in real time based on local frequency measurement so that the aggregated load response under each bus matches the desired power determined by the first layer.…”
Section: Executive Summarymentioning
confidence: 99%
“…This study leveraged an existing laboratory set-up that was created for the purpose of studying and comparing the performance of traditional demand response at the timescale of hours to more rapid modes at the timescale of seconds [24]. Each experiment in this study included testing of an 80-gallon class ERWH and HPWH, with the same scheduled draw pattern and water temperature set point.…”
Section: Hardware Setup Used For Experimentsmentioning
confidence: 99%