IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i20p6466-d652833.html
   My bibliography  Save this article

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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Marlene Ofelia Sanchez-Escobar & Julieta Noguez & Jose Martin Molina-Espinosa & Rafael Lozano-Espinosa & Genoveva Vargas-Solar, 2021. "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," Energies, MDPI, vol. 14(20), pages 1-28, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:20:p:6466-:d:652833
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/20/6466/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/20/6466/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mohseni, Amin & Mortazavi, Seyed Saeidollah & Ghasemi, Ahmad & Nahavandi, Ali & Talaei abdi, Masoud, 2017. "The application of household appliances' flexibility by set of sequential uninterruptible energy phases model in the day-ahead planning of a residential microgrid," Energy, Elsevier, vol. 139(C), pages 315-328.
    2. Pradhan, Bijay B. & Limmeechokchai, Bundit & Shrestha, Ram M., 2019. "Implications of biogas and electric cooking technologies in residential sector in Nepal – A long term perspective using AIM/Enduse model," Renewable Energy, Elsevier, vol. 143(C), pages 377-389.
    3. Hara, Keishiro & Uwasu, Michinori & Kishita, Yusuke & Takeda, Hiroyuki, 2015. "Determinant factors of residential consumption and perception of energy conservation: Time-series analysis by large-scale questionnaire in Suita, Japan," Energy Policy, Elsevier, vol. 87(C), pages 240-249.
    4. Wang, Xia & Feng, Wei & Cai, Weiguang & Ren, Hong & Ding, Chao & Zhou, Nan, 2019. "Do residential building energy efficiency standards reduce energy consumption in China? – A data-driven method to validate the actual performance of building energy efficiency standards," Energy Policy, Elsevier, vol. 131(C), pages 82-98.
    5. van Beeck, N.M.J.P., 1999. "Classification of Energy Models," Other publications TiSEM 6f2cbb5e-2d53-4be6-a4f9-9, Tilburg University, School of Economics and Management.
    6. Prina, Matteo Giacomo & Manzolini, Giampaolo & Moser, David & Nastasi, Benedetto & Sparber, Wolfram, 2020. "Classification and challenges of bottom-up energy system models - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 129(C).
    7. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.
    8. Levine, Mark D. & Koomey, Jonathan G. & Price, Lynn & Geller, Howard & Nadel, Steven, 1995. "Electricity end-use efficiency: Experience with technologies, markets, and policies throughout the world," Energy, Elsevier, vol. 20(1), pages 37-61.
    9. Radpour, Saeidreza & Hossain Mondal, Md Alam & Kumar, Amit, 2017. "Market penetration modeling of high energy efficiency appliances in the residential sector," Energy, Elsevier, vol. 134(C), pages 951-961.
    10. Schütz, Thomas & Schiffer, Lutz & Harb, Hassan & Fuchs, Marcus & Müller, Dirk, 2017. "Optimal design of energy conversion units and envelopes for residential building retrofits using a comprehensive MILP model," Applied Energy, Elsevier, vol. 185(P1), pages 1-15.
    11. Meangbua, Onicha & Dhakal, Shobhakar & Kuwornu, John K.M., 2019. "Factors influencing energy requirements and CO2 emissions of households in Thailand: A panel data analysis," Energy Policy, Elsevier, vol. 129(C), pages 521-531.
    12. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    13. Lundgren, Berndt & Schultzberg, Mårten, 2019. "Application of the economic theory of self-control to model energy conservation behavioral change in households," Working Paper Series 19/1, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance.
    14. Sergey Paltsev, 2017. "Energy scenarios: the value and limits of scenario analysis," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 6(4), July.
    15. Lundgren, Berndt & Schultzberg, Mårten, 2019. "Application of the economic theory of self-control to model energy conservation behavioral change in households," Energy, Elsevier, vol. 183(C), pages 536-546.
    16. Aydin, Erdal & Brounen, Dirk, 2019. "The impact of policy on residential energy consumption," Energy, Elsevier, vol. 169(C), pages 115-129.
    17. Krarti, Moncef & Aldubyan, Mohammad & Williams, Eric, 2020. "Residential building stock model for evaluating energy retrofit programs in Saudi Arabia," Energy, Elsevier, vol. 195(C).
    18. Andrea Herbst & Felipe Andrés Toro & Felix Reitze & Eberhard Jochem, 2012. "Introduction to Energy Systems Modelling," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 148(II), pages 111-135, June.
    19. van Beeck, N.M.J.P., 1999. "Classification of Energy Models," Research Memorandum 777, Tilburg University, School of Economics and Management.
    20. Iwaro, Joseph & Mwasha, Abraham, 2010. "A review of building energy regulation and policy for energy conservation in developing countries," Energy Policy, Elsevier, vol. 38(12), pages 7744-7755, December.
    21. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    22. Nejat, Payam & Jomehzadeh, Fatemeh & Taheri, Mohammad Mahdi & Gohari, Mohammad & Abd. Majid, Muhd Zaimi, 2015. "A global review of energy consumption, CO2 emissions and policy in the residential sector (with an overview of the top ten CO2 emitting countries)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 843-862.
    23. Varone, Frederic & Aebischer, Bernard, 2001. "Energy efficiency: the challenges of policy design," Energy Policy, Elsevier, vol. 29(8), pages 615-629, June.
    24. Dominic White & Niven Winchester, 2018. "Energy- and multi-sector modelling of climate change mitigation in New Zealand: current practice and future needs," Working Papers 18_15, Motu Economic and Public Policy Research.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. El-Sayed, Ahmed Hassan A. & Khalil, Adel & Yehia, Mohamed, 2023. "Modeling alternative scenarios for Egypt 2050 energy mix based on LEAP analysis," Energy, Elsevier, vol. 266(C).
    2. António Gomes Martins & Luís Pires Neves & José Luís Sousa, 2023. "Electricity Demand Side Management," Energies, MDPI, vol. 16(16), pages 1-3, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marlene Ofelia Sanchez-Escobar & Julieta Noguez & Jose Martin Molina-Espinosa & David Escobar-Castillejos & Sergio Ruiz-Loza, 2023. "Policy Design for Electricity Efficiency: A Case Study of Bottom-Up Energy Modeling in the Residential Sector and Buildings," Energies, MDPI, vol. 16(19), pages 1-39, September.
    2. Yoro, Kelvin O. & Daramola, Michael O. & Sekoai, Patrick T. & Wilson, Uwemedimo N. & Eterigho-Ikelegbe, Orevaoghene, 2021. "Update on current approaches, challenges, and prospects of modeling and simulation in renewable and sustainable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    3. Martínez-Gordón, R. & Morales-España, G. & Sijm, J. & Faaij, A.P.C., 2021. "A review of the role of spatial resolution in energy systems modelling: Lessons learned and applicability to the North Sea region," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    4. Prina, Matteo Giacomo & Manzolini, Giampaolo & Moser, David & Nastasi, Benedetto & Sparber, Wolfram, 2020. "Classification and challenges of bottom-up energy system models - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 129(C).
    5. Després, Jacques & Hadjsaid, Nouredine & Criqui, Patrick & Noirot, Isabelle, 2015. "Modelling the impacts of variable renewable sources on the power sector: Reconsidering the typology of energy modelling tools," Energy, Elsevier, vol. 80(C), pages 486-495.
    6. Thomas Pregger & Tobias Naegler & Wolfgang Weimer-Jehle & Sigrid Prehofer & Wolfgang Hauser, 2020. "Moving towards socio-technical scenarios of the German energy transition—lessons learned from integrated energy scenario building," Climatic Change, Springer, vol. 162(4), pages 1743-1762, October.
    7. Jacques Després & Patrick Criqui & Silvana Mima & Nouredine Hadjsaid & Isabelle Noirot, 2014. "Variable renewable energies and storage development in long term energy modelling tools," Post-Print hal-01279467, HAL.
    8. Thimet, P.J. & Mavromatidis, G., 2022. "Review of model-based electricity system transition scenarios: An analysis for Switzerland, Germany, France, and Italy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    9. Prina, Matteo Giacomo & Nastasi, Benedetto & Groppi, Daniele & Misconel, Steffi & Garcia, Davide Astiaso & Sparber, Wolfram, 2022. "Comparison methods of energy system frameworks, models and scenario results," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    10. Birgit A. Henrich & Thomas Hoppe & Devin Diran & Zofia Lukszo, 2021. "The Use of Energy Models in Local Heating Transition Decision Making: Insights from Ten Municipalities in The Netherlands," Energies, MDPI, vol. 14(2), pages 1-23, January.
    11. Blanco, Herib & Leaver, Jonathan & Dodds, Paul E. & Dickinson, Robert & García-Gusano, Diego & Iribarren, Diego & Lind, Arne & Wang, Changlong & Danebergs, Janis & Baumann, Martin, 2022. "A taxonomy of models for investigating hydrogen energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    12. Chang, Miguel & Thellufsen, Jakob Zink & Zakeri, Behnam & Pickering, Bryn & Pfenninger, Stefan & Lund, Henrik & Østergaard, Poul Alberg, 2021. "Trends in tools and approaches for modelling the energy transition," Applied Energy, Elsevier, vol. 290(C).
    13. Klemm, Christian & Vennemann, Peter, 2021. "Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    14. Malla, Sunil, 2022. "An outlook of end-use energy demand based on a clean energy and technology transformation of the household sector in Nepal," Energy, Elsevier, vol. 238(PB).
    15. Ilaria Perissi & Gianluca Martelloni & Ugo Bardi & Davide Natalini & Aled Jones & Angel Nikolaev & Lukas Eggler & Martin Baumann & Roger Samsó & Jordi Solé, 2021. "Cross-Validation of the MEDEAS Energy-Economy-Environment Model with the Integrated MARKAL-EFOM System (TIMES) and the Long-Range Energy Alternatives Planning System (LEAP)," Sustainability, MDPI, vol. 13(4), pages 1-27, February.
    16. Prina, Matteo Giacomo & Groppi, Daniele & Nastasi, Benedetto & Garcia, Davide Astiaso, 2021. "Bottom-up energy system models applied to sustainable islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    17. Natalia Gennadyevna Zakharchenko & Olga Valeryevna Dyomina, 2015. "Modelling Energy - Economy Interactions: The Far East Experience," Spatial Economics=Prostranstvennaya Ekonomika, Economic Research Institute, Far Eastern Branch, Russian Academy of Sciences (Khabarovsk, Russia), issue 1, pages 62-90.
    18. Koengkan, Matheus & Fuinhas, José Alberto & Osmani, Fariba & Kazemzadeh, Emad & Auza, Anna & Alavijeh, Nooshin Karimi & Teixeira, Mônica, 2022. "Do financial and fiscal incentive policies increase the energy efficiency ratings in residential properties? A piece of empirical evidence from Portugal," Energy, Elsevier, vol. 241(C).
    19. Vaccaro, Roberto & Rocco, Matteo V., 2021. "Quantifying the impact of low carbon transition scenarios at regional level through soft-linked energy and economy models: The case of South-Tyrol Province in Italy," Energy, Elsevier, vol. 220(C).
    20. Khan, Muhammad Arshad, 2015. "Modelling and forecasting the demand for natural gas in Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 1145-1159.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:20:p:6466-:d:652833. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.