Date of Award

2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Natural Resources

First Advisor

Brendan Fisher

Second Advisor

Christopher Koliba

Abstract

As the energy system embraces intermittent and renewable energy sources to achieve decarbonization goals, the residential sector is expected to play a more active role in managing energy. Future visions of the system view the residential home as a distributed and flexible energy resource, capable of dynamically shifting energy use in time to align with the availability of renewables. This will be supported by the diffusion of smart technologies with enhanced information-based and automated features to control energy use more granularly. Such a shift raises numerous questions: who should be tasked with managing energy use in the home and for what purposes; how is control over energy use defined and how will the introduction of smart technologies in the home shift who has it; and who may face barriers to accessing the benefits of such programs as policy strives to advance a more equitable energy future.

This dissertation aims to address these questions through developing interdisciplinary tools and analyses to support a holistic understanding of how smart home energy management systems (SHEMS) might impact the grid as a whole and the people for whom it was built to serve. First, I conduct a systematic meta-review on the smart home energy management system literature to understand dominant discourse around the implementation of SHEMS. Results show a body of research skewed towards techno-centric approaches to smart home energy management and a lack of integration between the social and technical disciplines. Second, I propose a multidisciplinary taxonomy of control in the smart home which defines control as both a function of technical automation and relationships between actors in the energy system. The outcome is a scenario analysis tool which defines four characteristic types of control and highlights core issues for consideration in each scenario based on illustrative case studies. Finally, I explore how indicators used to identify disadvantaged communities predict patterns of household activities and adoption of enabling technologies related to demand flexibility. Results show that income, race, education, housing type and tenure, age and disability significantly correlate with activity patterns and technology access. Based on these findings, I offer recommendations on how policy can better center equity as demand flexibility initiatives expand. In aggregate, this body of research critically reflects on how the human dimensions of energy use are currently being situated in SHEMS and demand flexibility research. It offers reflections on how future research and practice can holistically evaluate the implications of new innovations for diverse actors in the energy system.

Language

en

Number of Pages

210 p.

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