IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i13p4911-d1178058.html
   My bibliography  Save this article

Enhancing Survey Efficiency and Predictive Ability in Energy System Design through Machine Learning: A Workflow-Based Approach for Improved Outcomes

Author

Listed:
  • Andrew Chapman

    (International Institute for Carbon Neutral Energy Research (WPI-I2CNER), Kyushu University, Fukuoka 819-0395, Japan)

Abstract

The design of a desirable, sustainable energy system needs to consider a broad range of technologies, the market landscape, and the preferences of the population. In order to elicit these preferences, both toward lifestyle factors and energy system design, stakeholder engagement is critical. One popular method of stakeholder engagement is the deployment and subsequent analysis of a survey. However, significant time and resources are required to design, test, implement and analyze surveys. In the age of high data availability, it is likely that innovative approaches such as machine learning might be applied to datasets to elicit factors which underpin preferences toward energy systems and the energy mix. This research seeks to test this hypothesis, utilizing multiple algorithms and survey datasets to elicit common factors which are influential toward energy system preferences and energy system design factors. Our research has identified that machine learning models can predict response ranges based on preferences, knowledge levels, behaviors, and demographics toward energy system design in terms of technology deployment and important socio-economic factors. By applying these findings to future energy survey research design, it is anticipated that the burdens associated with survey design and implementation, as well as the burdens on respondents, can be significantly reduced.

Suggested Citation

  • Andrew Chapman, 2023. "Enhancing Survey Efficiency and Predictive Ability in Energy System Design through Machine Learning: A Workflow-Based Approach for Improved Outcomes," Energies, MDPI, vol. 16(13), pages 1-16, June.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:13:p:4911-:d:1178058
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/13/4911/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/13/4911/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Heffron, Raphael J. & McCauley, Darren, 2017. "The concept of energy justice across the disciplines," Energy Policy, Elsevier, vol. 105(C), pages 658-667.
    2. Manuel Frondel & Stephan Sommer & Colin Vance, 2015. "The burden of Germanyùs energy transition: An empirical analysis of distributional effects," Economic Analysis and Policy, Elsevier, vol. 45(c), pages 89-99.
    3. Perera, A.T.D. & Wickramasinghe, P.U. & Nik, Vahid M. & Scartezzini, Jean-Louis, 2019. "Machine learning methods to assist energy system optimization," Applied Energy, Elsevier, vol. 243(C), pages 191-205.
    4. Hugo Hanbury & Christoph Bader & Stephanie Moser, 2019. "Reducing Working Hours as a Means to Foster Low(er)-Carbon Lifestyles? An Exploratory Study on Swiss Employees," Sustainability, MDPI, vol. 11(7), pages 1-17, April.
    5. Dvarioniene, Jolanta & Gurauskiene, Inga & Gecevicius, Giedrius & Trummer, Dora Ruth & Selada, Catarina & Marques, Isabel & Cosmi, Carmelina, 2015. "Stakeholders involvement for energy conscious communities: The Energy Labs experience in 10 European communities," Renewable Energy, Elsevier, vol. 75(C), pages 512-518.
    6. Fragkos, Panagiotis & Fragkiadakis, Kostas & Sovacool, Benjamin & Paroussos, Leonidas & Vrontisi, Zoi & Charalampidis, Ioannis, 2021. "Equity implications of climate policy: Assessing the social and distributional impacts of emission reduction targets in the European Union," Energy, Elsevier, vol. 237(C).
    7. repec:zbw:rwirep:0542 is not listed on IDEAS
    8. Stephen Smith & Angela Jaszczak & Jessica Graber & Katie Lundeen & Sara Leitsch & Erin Wargo & Colm O'Muircheartaigh, 2009. "Instrument Development, Study Design Implementation, and Survey Conduct for the National Social Life, Health, and Aging Project," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 64(suppl_1), pages 20-29.
    9. Itaoka, Kenshi & Chapman, Andrew & Farabi-Asl, Hadi, 2022. "Underpinnings of consumer preferences and participation in Japan's liberalized energy market," Utilities Policy, Elsevier, vol. 76(C).
    10. Perera, A.T.D. & Wickramasinghe, P.U. & Nik, Vahid M. & Scartezzini, Jean-Louis, 2020. "Introducing reinforcement learning to the energy system design process," Applied Energy, Elsevier, vol. 262(C).
    11. Goddard, George & Farrelly, Megan A., 2018. "Just transition management: Balancing just outcomes with just processes in Australian renewable energy transitions," Applied Energy, Elsevier, vol. 225(C), pages 110-123.
    12. Chapman, Andrew & Shigetomi, Yosuke & Karmaker, Shamal Chandra & Saha, Bidyut & Brooks, Caleb, 2022. "Cultural and demographic energy system awareness and preference: Implications for future energy system design in the United States," Energy Economics, Elsevier, vol. 112(C).
    Full references (including those not matched with items on IDEAS)

    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. Nik, Vahid M. & Moazami, Amin, 2021. "Using collective intelligence to enhance demand flexibility and climate resilience in urban areas," Applied Energy, Elsevier, vol. 281(C).
    2. Prina, Matteo Giacomo & Dallapiccola, Mattia & Moser, David & Sparber, Wolfram, 2024. "Machine learning as a surrogate model for EnergyPLAN: Speeding up energy system optimization at the country level," Energy, Elsevier, vol. 307(C).
    3. Kim, Sunwoo & Choi, Yechan & Park, Joungho & Adams, Derrick & Heo, Seongmin & Lee, Jay H., 2024. "Multi-period, multi-timescale stochastic optimization model for simultaneous capacity investment and energy management decisions for hybrid Micro-Grids with green hydrogen production under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
    4. Van Uffelen, N. & Taebi, B. & Pesch, Udo, 2024. "Revisiting the energy justice framework: Doing justice to normative uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    5. Frondel Manuel & Kutzschbauch Ole & Sommer Stephan & Traub Stefan, 2017. "Die Gerechtigkeitslücke in der Verteilung der Kosten der Energiewende auf die privaten Haushalte," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 18(4), pages 335-347, November.
    6. Wang, Zhengchao & Perera, A.T.D., 2020. "Integrated platform to design robust energy internet," Applied Energy, Elsevier, vol. 269(C).
    7. Machado E Silva, Isabela Morbach & Medeiros Costa, Hirdan Katarina de, 2019. "Brazilian Social Funds: The lessons learned from the Norway fund experience," Energy Policy, Elsevier, vol. 129(C), pages 161-167.
    8. Di Leo, Senatro & Salvia, Monica, 2017. "Local strategies and action plans towards resource efficiency in South East Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 286-305.
    9. Radtke, Jörg & Scherhaufer, Patrick, 2022. "A social science perspective on conflicts in the energy transition: An introduction to the special issue," Utilities Policy, Elsevier, vol. 78(C).
    10. Gerd Lupp & Aude Zingraff-Hamed & Josh J. Huang & Amy Oen & Stephan Pauleit, 2020. "Living Labs—A Concept for Co-Designing Nature-Based Solutions," Sustainability, MDPI, vol. 13(1), pages 1-22, December.
    11. Lan, Penghang & Chen, She & Li, Qihang & Li, Kelin & Wang, Feng & Zhao, Yaoxun, 2024. "Intelligent hydrogen-ammonia combined energy storage system with deep reinforcement learning," Renewable Energy, Elsevier, vol. 237(PB).
    12. Jeuland, Marc & Fetter, T. Robert & Li, Yating & Pattanayak, Subhrendu K. & Usmani, Faraz & Bluffstone, Randall A. & Chávez, Carlos & Girardeau, Hannah & Hassen, Sied & Jagger, Pamela & Jaime, Mónica , 2021. "Is energy the golden thread? A systematic review of the impacts of modern and traditional energy use in low- and middle-income countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    13. Elias Carayannis & Pantelis Kostis & Hasan Dinçer & Serhat Yüksel, 2024. "Quality Function Deployment-Oriented Strategic Outlook to Sustainable Energy Policies Based on Quintuple Innovation Helix," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 6761-6779, June.
    14. Liang, Liang & Wu, Xuanyu & Yang, Min, 2025. "Shadows behind the sun: Inequity caused by rooftop solar and responses to it," Applied Energy, Elsevier, vol. 377(PB).
    15. Poncian, Japhace & Jose, Jim, 2019. "National resource ownership and community engagement in Tanzania's natural gas governance," Energy Policy, Elsevier, vol. 133(C).
    16. Andor, Mark Andreas & Frondel, Manuel & Sommer, Stephan, 2015. "Reform des EU-Emissionshandels: Alternativen zur Marktstabilitätsreserve," RWI Materialien 87, RWI - Leibniz-Institut für Wirtschaftsforschung.
    17. Sumarno, Theresia B. & Sihotang, Parulian & Prawiraatmadja, Widhyawan, 2022. "Exploring Indonesia's energy policy failures through the JUST framework," Energy Policy, Elsevier, vol. 164(C).
    18. Chepeliev, Maksym & Osorio-Rodarte, Israel & van der Mensbrugghe, Dominique, 2021. "Distributional impacts of carbon pricing policies under the Paris Agreement: Inter and intra-regional perspectives," Energy Economics, Elsevier, vol. 102(C).
    19. Zhang, Shaobin & Shi, Baofeng & Ji, Hao, 2023. "How to decouple income growth from household carbon emissions: A perspective based on urban-rural differences in China," Energy Economics, Elsevier, vol. 125(C).
    20. Andor, Mark A. & Lange, Andreas & Sommer, Stephan, 2022. "Fairness and the support of redistributive environmental policies," Journal of Environmental Economics and Management, Elsevier, vol. 114(C).

    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:16:y:2023:i:13:p:4911-:d:1178058. 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.