The Contribution of Bottom-Up Energy Models to Support Policy Design of Electricity End-Use Efficiency for Residential Buildings and the Residential Sector: A Systematic Review

Marlene Ofelia Sanchez-Escobar, Julieta Noguez, Jose Martin Molina-Espinosa, Rafael Lozano-Espinosa and Genoveva Vargas-Solar
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Marlene Ofelia Sanchez-Escobar: Tecnologico de Monterrey, School of Engineering and Science, Ave. Eugenio Garza Sada 2501, Monterrey 64849, NL, Mexico
Julieta Noguez: Tecnologico de Monterrey, School of Engineering and Science, Ave. Eugenio Garza Sada 2501, Monterrey 64849, NL, Mexico
Jose Martin Molina-Espinosa: Tecnologico de Monterrey, School of Engineering and Science, Ave. Eugenio Garza Sada 2501, Monterrey 64849, NL, Mexico
Rafael Lozano-Espinosa: Tecnologico de Monterrey, School of Engineering and Science, Ave. Eugenio Garza Sada 2501, Monterrey 64849, NL, Mexico
Genoveva Vargas-Solar: LIRIS UMR5205, CNRS, 69621 Villeurbanne, France

Energies, 2021, vol. 14, issue 20, 1-28

Abstract: Bottom-up energy models are considered essential tools to support policy design of electricity end-use efficiency. However, in the literature, no study analyzes their contribution to support policy design of electricity end-use efficiency, the modeling techniques used to build them, and the policy instruments supported by them. This systematic review fills that gap by identifying the current capability of bottom-up energy models to support specific policy instruments. In the research, we review 192 publications from January 2015 to June 2020 to finally select 20 for further examination. The articles are analyzed quantitatively in terms of techniques, model characteristics, and applied policies. The findings of the study reveal that: (1) bottom-up energy models contribute to the support of policy design of electricity end-use efficiency with the application of specific best practices (2) bottom-up energy models do not provide a portfolio of analytical methods which constraint their capability to support policy design (3) bottom-up energy models for residential buildings have limited policy support and (4) bottom-up energy models’ design reveals a lack of inclusion of key energy efficiency metrics to support decision-making. This study’s findings can help researchers and energy modelers address these limitations and create new models following best practices.

Keywords: energy modelling; electricity efficiency; energy policy; residential buildings; households; data-driven approach (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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