文章基本信息

标题：Translating observed household energy behavior to agent-based technology choices in an integrated modeling framework
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作者：Oreane.Y. Edelenbosch ; Luciana Miu ; Julia Sachs 等
期刊名称：iScience
印刷版ISSN：2589-0042
出版年度：2022
卷号：25
期号：3
页码：1-23
DOI：10.1016/j.isci.2022.103905
语种：English
出版社：Elsevier
摘要：SummaryDecarbonizing the building sector depends on choices made at the household level, which are heterogeneous. Agent-based models are tools used to describe heterogeneous choices but require data-intensive calibration. This study analyzes a novel, cross-country European household-level survey, including sociodemographic characteristics, energy-saving habits, energy-saving investments, and metered household electricity consumption, to enhance the empirical grounding of an agent-based residential energy choice model. Applying cluster analysis to the data shows that energy consumption is not straightforwardly explained by sociodemographic classes, preferences, or attitudes, but some patterns emerge. Income consistently has the largest effect on demand, dwelling efficiency, and energy-saving investments, and the potential to improve a dwellings' energy use affects the efficiency investments made. Including the various sources of heterogeneity found to characterize the model agents affects the timing and speed of the transition. The results reinforce the need for grounding agent-based models in empirical data, to better understand energy transition dynamics.Graphical abstractDisplay OmittedHighlights•Household survey data used to enhance empirical grounding of agent based model•New method developed to translate survey questions to model parameters•Sociodemographics and perspectives do not easily explain consumption behavior•Income has largest effect on demand, efficiency and energy-saving investmentsEnergy sustainability; Energy Resources; Energy systems