A critical review of heat pump adoption in empirical and modeling literature

20337 6 108624 2 329182 document 108624 1-s2.0-S2589004224028931-main.pdf application/pdf dd357da0e8891e1179673836b35f32b5 MD5 744841 2025-01-13 09:56:28 https://pure.iiasa.ac.at/id/eprint/20337/1/1-s2.0-S2589004224028931-main.pdf 20337 1 1 application/pdf text en public cc_by_4

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published 108631 1 329205 document 108631 indexcodes.txt text/x-c d74caae688a1a49d7b80596d3e91a978 MD5 17103 2025-01-13 10:06:43 https://pure.iiasa.ac.at/id/eprint/20337/2/indexcodes.txt 20337 2 2 text/x-c other Generate index codes conversion from text to indexcodes en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/108624 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/108624 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/108624 archive 353 disk0/00/02/03/37 2025-01-13 09:58:55 2025-01-13 09:58:55 2025-01-13 09:58:55 article show Rao N. 1961 0000-0003-1888-5292 Siam M.R.K. Bond T.C. A critical review of heat pump adoption in empirical and modeling literature pub ECE TISS Energy policy, Engineering, Energy systems Household electrification is an important pillar of decarbonization in the US and requires the rapid adoption of electric heat pumps. Household energy models that project adoption rates do not represent these decisions well. To what extent are they limited by fundamental knowledge gaps, or is there scope to incorporate insights from the social science literature? We review the energy modeling and social science literature on heating equipment adoption to synthesize our understanding of adoption decisions, to identify best practices on representing decision-making behavior among energy models, and to suggest model improvements. At the most aggregated level, market allocation models divide market shares among different technologies by considering a single representative household, ignoring heterogeneity among the actors. Energy-system models and agent-based models can include some disaggregation. Adoption decisions include two stages, one to retire existing equipment, and to select the preferred technology. Equipment breaking down, price shocks, and moving to a new house promote entering the first stage, but these factors are not widely explored in surveys. The empirical literature reveals considerable heterogeneity in what matters to people in choosing technology. Even cost considerations, which are the most widespread, vary in the components and the manner in which they enter decisions. Other considerations include comfort and reliability; whether decision-makers are urban, young and educated; and how adopters perceive novel technologies. However, the relative strengths of these factors and how they vary across the US population are not known. Modelers can make incremental structural improvements such as separating the two decision stages, differentiating household groups, and incorporating changing household perceptions with market maturation. However, they cannot ground these in reality without considerable new fieldwork on decision-making processes and their variation across the population. 2025-01-17 published doi:10.1016/j.isci.2024.111666 243 public iScience 28 1 e111666 TRUE 2589-0042 no info:eu-repo/semantics/article