Dirty dishes or dirty laundry? Comparing two methods for quantifying American consumers' preferences for load management in a smart home

Aloise-Young, Patricia A.; Lurbe, Salvador; Isley, Steven; Kadavil, Rahul; Suryanarayanan, Siddharth; Christensen, Dane

doi:10.1016/j.erss.2020.101781

Title: Dirty dishes or dirty laundry? Comparing two methods for quantifying American consumers' preferences for load management in a smart home

Journal Article · Tue Nov 10 00:00:00 EST 2020 · Energy Research and Social Science

DOI:https://doi.org/10.1016/j.erss.2020.101781· OSTI ID:1726046

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Colorado State Univ., Fort Collins, CO (United States)
National Renewable Energy Lab. (NREL), Golden, CO (United States)
South Dakota State Univ., Brookings, SD (United States)

One challenge of transitioning to renewable energy is that household electricity use and renewable generation are often misaligned. Smart home energy management systems hold promise for shifting usage to match generation, but these systems need to be designed with the occupants’ preferences in mind. The purpose of the present research is to compare two approaches for collecting and modeling consumers’ load management preferences, both of which are amenable to use in a home energy management system. Specifically, we examine the performance of Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER) and Analytic Hierarchy Process (AHP) in quantifying consumers’ preferences regarding air temperature (air conditioning and heating), water heating, dishwashing, clothes washing and drying, monetary costs, environmental impacts, and comfort/convenience. Two studies are presented: Study 1 examines the SMARTER approach, and Study 2 focuses on the AHP approach. In both studies, online surveys (N_SMARTER = 956 and N_AHP = 1023) were conducted to elicit preferences from participants across the United States. The preferences modeled by both approaches were validated based on (a) their ability to predict participants’ choices in a Discrete Choice Experiment and (b) their convergence with previous research on load-shifting behavior. The validation procedure suggests that the SMARTER approach is superior in modeling consumers’ preferences for load management. Overall, this research lays the groundwork for designing a smart home interface capable of collecting occupants’ preferences and using those preferences to deliver improved occupant comfort, lower operating costs, reduced environmental impact, and more significant demand response than exists today.

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Research Organization:: National Renewable Energy Lab. (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office; Bonneville Power Administration

Grant/Contract Number:: AC36-08GO28308; TIP-337

OSTI ID:: 1726046

Report Number(s):: NREL/JA-5R00-77713; MainId:30628; UUID:08362cb7-faa5-4982-849d-5605d790871b; MainAdminID:18865

Journal Information:: Energy Research and Social Science, Vol. 71; ISSN 2214-6296

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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