Translating observed household energy behavior to agent-based technology choices in an integrated modeling framework

Oreane Y. Edelenbosch; Luciana Miu; Julia Sachs; Adam Hawkes; Massimo Tavoni

doi:10.1016/j.isci.2022.103905

Translating observed household energy behavior to agent-based technology choices in an integrated modeling framework

Oreane Y. Edelenbosch^*
, Luciana Miu
, Julia Sachs
, Adam Hawkes
, Massimo Tavoni

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Decarbonizing 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.

Original language	English
Article number	103905
Pages (from-to)	1-22
Journal	iScience
Volume	25
Issue number	3
DOIs	https://doi.org/10.1016/j.isci.2022.103905
Publication status	Published - 18 Mar 2022

Bibliographical note

Funding Information:
O.E. and M.T. acknowledge financial support from the European Research Council under the European Union’s Seventh Framework Programme ( FP7/2007-2013 )/ ERC grant agreement no. 154 336155 - project COBHAM “The role of consumer behaviour and heterogeneity in the integrated assessment of energy and climate policies.” A.H. acknowledges support from the H2020 European Commission Project PARIS REINFORCE (grant no. 820846 ).

Funding Information:
O.E. and M.T. acknowledge financial support from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no. 154 336155 - project COBHAM “The role of consumer behaviour and heterogeneity in the integrated assessment of energy and climate policies.” A.H. acknowledges support from the H2020 European Commission Project PARIS REINFORCE (grant no. 820846). This project was conceived by A.H. and M.T. L.M. compiled the majority of data used in the analysis and applied the cluster analysis. J.S. developed the RSBM model and translated the outcomes of the cluster analysis to the RSBM model. O.E. wrote the literature review, took the lead in writing, and connected the data analysis to the modeling. All authors provided critical feedback and helped shape the research analysis, data presentation, and manuscript. The authors declare no competing interests. The authors have no financial or nonfinancial interests associated with the material in this manuscript.

Publisher Copyright:
© 2022 The Author(s)

Funding

O.E. and M.T. acknowledge financial support from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no. 154 336155 - project COBHAM ?The role of consumer behaviour and heterogeneity in the integrated assessment of energy and climate policies.? A.H. acknowledges support from the H2020 European Commission Project PARIS REINFORCE (grant no. 820846). This project was conceived by A.H. and M.T. L.M. compiled the majority of data used in the analysis and applied the cluster analysis. J.S. developed the RSBM model and translated the outcomes of the cluster analysis to the RSBM model. O.E. wrote the literature review, took the lead in writing, and connected the data analysis to the modeling. All authors provided critical feedback and helped shape the research analysis, data presentation, and manuscript. The authors declare no competing interests. The authors have no financial or nonfinancial interests associated with the material in this manuscript. O.E. and M.T. acknowledge financial support from the European Research Council under the European Union’s Seventh Framework Programme ( FP7/2007-2013 )/ ERC grant agreement no. 154 336155 - project COBHAM “The role of consumer behaviour and heterogeneity in the integrated assessment of energy and climate policies.” A.H. acknowledges support from the H2020 European Commission Project PARIS REINFORCE (grant no. 820846 ).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Energy Resources
Energy sustainability
Energy systems

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10.1016/j.isci.2022.103905Licence: CC BY

PIIS2589004222001754Final published version, 2.69 MBLicence: CC BY

Cite this

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title = "Translating observed household energy behavior to agent-based technology choices in an integrated modeling framework",

abstract = "Decarbonizing 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.",

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N1 - Funding Information: O.E. and M.T. acknowledge financial support from the European Research Council under the European Union’s Seventh Framework Programme ( FP7/2007-2013 )/ ERC grant agreement no. 154 336155 - project COBHAM “The role of consumer behaviour and heterogeneity in the integrated assessment of energy and climate policies.” A.H. acknowledges support from the H2020 European Commission Project PARIS REINFORCE (grant no. 820846 ). Funding Information: O.E. and M.T. acknowledge financial support from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no. 154 336155 - project COBHAM “The role of consumer behaviour and heterogeneity in the integrated assessment of energy and climate policies.” A.H. acknowledges support from the H2020 European Commission Project PARIS REINFORCE (grant no. 820846). This project was conceived by A.H. and M.T. L.M. compiled the majority of data used in the analysis and applied the cluster analysis. J.S. developed the RSBM model and translated the outcomes of the cluster analysis to the RSBM model. O.E. wrote the literature review, took the lead in writing, and connected the data analysis to the modeling. All authors provided critical feedback and helped shape the research analysis, data presentation, and manuscript. The authors declare no competing interests. The authors have no financial or nonfinancial interests associated with the material in this manuscript. Publisher Copyright: © 2022 The Author(s)

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AB - Decarbonizing 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.

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KW - Energy systems

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ER -

Translating observed household energy behavior to agent-based technology choices in an integrated modeling framework

Abstract

Bibliographical note

Funding

UN SDGs

Keywords

Access to Document

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