IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v172y2019icp752-768.html
   My bibliography  Save this article

An agent-based model for energy investment decisions in the residential sector

Author

Listed:
  • Sachs, Julia
  • Meng, Yiming
  • Giarola, Sara
  • Hawkes, Adam

Abstract

Energy-related investment decisions in the buildings sector are heterogeneous in that the outcome for each individual varies according to budget, values, and perception of a technology, even if an apparently identical decision task is faced. In particular, the rate of adoption of new energy-efficient technologies is often hard to model and underlines the need for an advanced approach to capture diversity in decision-making, and enable the inclusion of economic, comfort, environmental and social aspects. This paper presents an enhanced agent-based model that captures several characteristics of consumer behaviour that influence investment decisions. Multiple agents with different objectives, search strategies, and decision methods are implemented. A case study is presented which illustrates the benefits of the approach for the residential sector in the UK. The agent-based method shows diversity in investment decisions, without requiring the constraints on uptake needed in many models. This leads to a range of technologies in the market during a transition phase, continuous investment in low capital cost technologies, and eventually the emergence of a low carbon system based on new mass market technologies. The system that emerges is vastly different from one observed when economically rational investment is assumed and uptake constraints are applied.

Suggested Citation

  • Sachs, Julia & Meng, Yiming & Giarola, Sara & Hawkes, Adam, 2019. "An agent-based model for energy investment decisions in the residential sector," Energy, Elsevier, vol. 172(C), pages 752-768.
  • Handle: RePEc:eee:energy:v:172:y:2019:i:c:p:752-768
    DOI: 10.1016/j.energy.2019.01.161
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054421930177X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2019.01.161?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nair, Gireesh & Gustavsson, Leif & Mahapatra, Krushna, 2010. "Factors influencing energy efficiency investments in existing Swedish residential buildings," Energy Policy, Elsevier, vol. 38(6), pages 2956-2963, June.
    2. Valentina Bosetti & Carlo Carraro & Marzio Galeotti & Emanuele Massetti & Massimo Tavoni, 2006. "WITCH. A World Induced Technical Change Hybrid Model," Working Papers 2006_46, Department of Economics, University of Venice "Ca' Foscari".
    3. Barr, Stewart & Gilg, Andrew W & Ford, Nicholas, 2005. "The household energy gap: examining the divide between habitual- and purchase-related conservation behaviours," Energy Policy, Elsevier, vol. 33(11), pages 1425-1444, July.
    4. Cayla, Jean-Michel & Maïzi, Nadia, 2015. "Integrating household behavior and heterogeneity into the TIMES-Households model," Applied Energy, Elsevier, vol. 139(C), pages 56-67.
    5. Islam, Towhidul, 2014. "Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data," Energy Policy, Elsevier, vol. 65(C), pages 340-350.
    6. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    7. Ramea, Kalai & Bunch, David S. & Yang, Christopher & Yeh, Sonia & Ogden, Joan M., 2018. "Integration of behavioral effects from vehicle choice models into long-term energy systems optimization models," Energy Economics, Elsevier, vol. 74(C), pages 663-676.
    8. Kowsari, Reza & Zerriffi, Hisham, 2011. "Three dimensional energy profile:," Energy Policy, Elsevier, vol. 39(12), pages 7505-7517.
    9. Wilkerson, Jordan T. & Cullenward, Danny & Davidian, Danielle & Weyant, John P., 2013. "End use technology choice in the National Energy Modeling System (NEMS): An analysis of the residential and commercial building sectors," Energy Economics, Elsevier, vol. 40(C), pages 773-784.
    10. Richard Loulou & Maryse Labriet, 2008. "ETSAP-TIAM: the TIMES integrated assessment model Part I: Model structure," Computational Management Science, Springer, vol. 5(1), pages 7-40, February.
    11. Achtnicht, Martin & Madlener, Reinhard, 2014. "Factors influencing German house owners' preferences on energy retrofits," Energy Policy, Elsevier, vol. 68(C), pages 254-263.
    12. Steven T. Berry, 1994. "Estimating Discrete-Choice Models of Product Differentiation," RAND Journal of Economics, The RAND Corporation, vol. 25(2), pages 242-262, Summer.
    13. Chaudry, Modassar & Abeysekera, Muditha & Hosseini, Seyed Hamid Reza & Jenkins, Nick & Wu, Jianzhong, 2015. "Uncertainties in decarbonising heat in the UK," Energy Policy, Elsevier, vol. 87(C), pages 623-640.
    14. Sopha, Bertha Maya & Klöckner, Christian A. & Skjevrak, Geir & Hertwich, Edgar G., 2010. "Norwegian households' perception of wood pellet stove compared to air-to-air heat pump and electric heating," Energy Policy, Elsevier, vol. 38(7), pages 3744-3754, July.
    15. Richard Loulou, 2008. "ETSAP-TIAM: the TIMES integrated assessment model. part II: mathematical formulation," Computational Management Science, Springer, vol. 5(1), pages 41-66, February.
    16. Daniel Kahneman, 2003. "Maps of Bounded Rationality: Psychology for Behavioral Economics," American Economic Review, American Economic Association, vol. 93(5), pages 1449-1475, December.
    17. Valentina Bosetti, Carlo Carraro, Marzio Galeotti, Emanuele Massetti, Massimo Tavoni, 2006. "A World induced Technical Change Hybrid Model," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 13-38.
    18. Banfi, Silvia & Farsi, Mehdi & Filippini, Massimo & Jakob, Martin, 2008. "Willingness to pay for energy-saving measures in residential buildings," Energy Economics, Elsevier, vol. 30(2), pages 503-516, March.
    19. Palmer, J. & Sorda, G. & Madlener, R., 2015. "Modeling the diffusion of residential photovoltaic systems in Italy: An agent-based simulation," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 106-131.
    20. Zhang, Tao & Zhang, David, 2007. "Agent-based simulation of consumer purchase decision-making and the decoy effect," Journal of Business Research, Elsevier, vol. 60(8), pages 912-922, August.
    21. Stephenson, Janet & Barton, Barry & Carrington, Gerry & Gnoth, Daniel & Lawson, Rob & Thorsnes, Paul, 2010. "Energy cultures: A framework for understanding energy behaviours," Energy Policy, Elsevier, vol. 38(10), pages 6120-6129, October.
    22. Mahapatra, Krushna & Gustavsson, Leif, 2008. "An adopter-centric approach to analyze the diffusion patterns of innovative residential heating systems in Sweden," Energy Policy, Elsevier, vol. 36(2), pages 577-590, February.
    23. Berger, Thomas, 2001. "Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis," Agricultural Economics, Blackwell, vol. 25(2-3), pages 245-260, September.
    24. J. Doyne Farmer & Duncan Foley, 2009. "The economy needs agent-based modelling," Nature, Nature, vol. 460(7256), pages 685-686, August.
    25. Labay, Duncan G & Kinnear, Thomas C, 1981. "Exploring the Consumer Decision Process in the Adoption of Solar Energy Systems," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 8(3), pages 271-278, December.
    26. Li, Pei-Hao & Keppo, Ilkka & Strachan, Neil, 2018. "Incorporating homeowners' preferences of heating technologies in the UK TIMES model," Energy, Elsevier, vol. 148(C), pages 716-727.
    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. Giarola, Sara & Molar-Cruz, Anahi & Vaillancourt, Kathleen & Bahn, Olivier & Sarmiento, Luis & Hawkes, Adam & Brown, Maxwell, 2021. "The role of energy storage in the uptake of renewable energy: A model comparison approach," Energy Policy, Elsevier, vol. 151(C).
    2. Meles, Tensay Hadush & Ryan, Lisa, 2022. "Adoption of renewable home heating systems: An agent-based model of heat pumps in Ireland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    3. Olympios, Andreas V. & Pantaleo, Antonio M. & Sapin, Paul & Markides, Christos N., 2020. "On the value of combined heat and power (CHP) systems and heat pumps incentralised and distributed heating systems: Lessons from multi-fidelitymodelling approaches," Applied Energy, Elsevier, vol. 274(C).
    4. Matschegg, Doris & Carlon, Elisa & Sturmlechner, Rita & Sonnleitner, Andrea & Fuhrmann, Marilene & Dißauer, Christa & Strasser, Christoph & Enigl, Monika, 2023. "Investigation of individual motives and decision paths on residential energy supply systems," Energy, Elsevier, vol. 281(C).
    5. Flower, Jack & Hawker, Graeme & Bell, Keith, 2020. "Heterogeneity of UK residential heat demand and its impact on the value case for heat pumps," Energy Policy, Elsevier, vol. 144(C).
    6. Brown, Maxwell & Siddiqui, Sauleh & Avraam, Charalampos & Bistline, John & Decarolis, Joseph & Eshraghi, Hadi & Giarola, Sara & Hansen, Matthew & Johnston, Peter & Khanal, Saroj & Molar-Cruz, Anahi, 2021. "North American energy system responses to natural gas price shocks," Energy Policy, Elsevier, vol. 149(C).
    7. Besagni, Giorgio & Borgarello, Marco & Premoli Vilà, Lidia & Najafi, Behzad & Rinaldi, Fabio, 2020. "MOIRAE – bottom-up MOdel to compute the energy consumption of the Italian REsidential sector: Model design, validation and evaluation of electrification pathways," Energy, Elsevier, vol. 211(C).
    8. Moya, Diego & Budinis, Sara & Giarola, Sara & Hawkes, Adam, 2020. "Agent-based scenarios comparison for assessing fuel-switching investment in long-term energy transitions of the India’s industry sector," Applied Energy, Elsevier, vol. 274(C).
    9. Miu, Luciana & Hawkes, Adam D., 2020. "Private landlords and energy efficiency: Evidence for policymakers from a large-scale study in the United Kingdom," Energy Policy, Elsevier, vol. 142(C).
    10. Shi, Yingying & Wei, Zixiang & Shahbaz, Muhammad & Zeng, Yongchao, 2021. "Exploring the dynamics of low-carbon technology diffusion among enterprises: An evolutionary game model on a two-level heterogeneous social network," Energy Economics, Elsevier, vol. 101(C).
    11. Sara Giarola & Alexander Kell & Sonja Sechi & Mattia Carboni & Alaize Dall-Orsoletta & Pierluigi Leone & Adam Hawkes, 2023. "Sustainability Education: Capacity Building Using the MUSE Model," Energies, MDPI, vol. 16(14), pages 1-22, July.
    12. Hui, Wang & Xin-gang, Zhao & Ling-zhi, Ren & Fan, Lu, 2021. "An agent-based modeling approach for analyzing the influence of market participants’ strategic behavior on green certificate trading," Energy, Elsevier, vol. 218(C).
    13. 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).
    14. Rhodes, Ekaterina & Hoyle, Aaron & McPherson, Madeleine & Craig, Kira, 2022. "Understanding climate policy projections: A scoping review of energy-economy models in Canada," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    15. Benedikt Maciosek & Mehdi Farsi & Sylvain Weber & Martin Jakob, 2022. "Impact of complexity and experience on energy investment decisions for residential buildings," IRENE Working Papers 22-07, IRENE Institute of Economic Research.
    16. Volpe, R. & Catrini, P. & Piacentino, A. & Fichera, A., 2022. "An agent-based model to support the preliminary design and operation of heating and power grids with cogeneration units and photovoltaic panels in densely populated areas," Energy, Elsevier, vol. 261(PB).

    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. Wilson, C. & Pettifor, H. & Chryssochoidis, G., 2018. "Quantitative modelling of why and how homeowners decide to renovate energy efficiently," Applied Energy, Elsevier, vol. 212(C), pages 1333-1344.
    2. Elisha R. Frederiks & Karen Stenner & Elizabeth V. Hobman, 2015. "The Socio-Demographic and Psychological Predictors of Residential Energy Consumption: A Comprehensive Review," Energies, MDPI, vol. 8(1), pages 1-37, January.
    3. Ciola, Emanuele & Turco, Enrico & Gurgone, Andrea & Bazzana, Davide & Vergalli, Sergio & Menoncin, Francesco, 2022. "Charging the macroeconomy with an energy sector: an agent-based model," FEEM Working Papers 319877, Fondazione Eni Enrico Mattei (FEEM).
    4. Ciola, Emanuele & Turco, Enrico & Gurgone, Andrea & Bazzana, Davide & Vergalli, Sergio & Menoncin, Francesco, 2023. "Enter the MATRIX model:a Multi-Agent model for Transition Risks with application to energy shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    5. Klöckner, Christian A. & Nayum, Alim, 2017. "Psychological and structural facilitators and barriers to energy upgrades of the privately owned building stock," Energy, Elsevier, vol. 140(P1), pages 1005-1017.
    6. Knobloch, Florian & Pollitt, Hector & Chewpreecha, Unnada & Lewney, Richard & Huijbregts, Mark A.J. & Mercure, Jean-Francois, 2021. "FTT:Heat — A simulation model for technological change in the European residential heating sector," Energy Policy, Elsevier, vol. 153(C).
    7. Côté, Elizabeth & Pons-Seres de Brauwer, Cristian, 2023. "Preferences of homeowners for heat-pump leasing: Evidence from a choice experiment in France, Germany, and Switzerland," Energy Policy, Elsevier, vol. 183(C).
    8. Hiromi Yamamoto & Masahiro Sugiyama & Junichi Tsutsui, 2014. "Role of end-use technologies in long-term GHG reduction scenarios developed with the BET model," Climatic Change, Springer, vol. 123(3), pages 583-596, April.
    9. Hecher, Maria & Hatzl, Stefanie & Knoeri, Christof & Posch, Alfred, 2017. "The trigger matters: The decision-making process for heating systems in the residential building sector," Energy Policy, Elsevier, vol. 102(C), pages 288-306.
    10. Ce Huang & Jiefang Ma & Kun Song, 2021. "Homeowners’ Willingness to Make Investment in Energy Efficiency Retrofit of Residential Buildings in China and Its Influencing Factors," Energies, MDPI, vol. 14(5), pages 1-17, February.
    11. Henningsen, Geraldine & Wiese, Catharina, 2019. "Do Household Characteristics Really Matter? A Meta-Analysis on the Determinants of Households’ Energy-Efficiency Investments," MPRA Paper 101701, University Library of Munich, Germany.
    12. Gjorgiev, Blazhe & Garrison, Jared B. & Han, Xuejiao & Landis, Florian & van Nieuwkoop, Renger & Raycheva, Elena & Schwarz, Marius & Yan, Xuqian & Demiray, Turhan & Hug, Gabriela & Sansavini, Giovanni, 2022. "Nexus-e: A platform of interfaced high-resolution models for energy-economic assessments of future electricity systems," Applied Energy, Elsevier, vol. 307(C).
    13. Fischbacher, Urs & Schudy, Simeon & Teyssier, Sabrina, 2021. "Heterogeneous preferences and investments in energy saving measures," Resource and Energy Economics, Elsevier, vol. 63(C).
    14. Blanco, Herib & Gómez Vilchez, Jonatan J. & Nijs, Wouter & Thiel, Christian & Faaij, André, 2019. "Soft-linking of a behavioral model for transport with energy system cost optimization applied to hydrogen in EU," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    15. Meles, Tensay Hadush & Ryan, Lisa & Mukherjee, Sanghamitra C., 2022. "Heterogeneity in preferences for renewable home heating systems among Irish households," Applied Energy, Elsevier, vol. 307(C).
    16. Christian A. Oberst & Reinhard Madlener, 2015. "Prosumer Preferences Regarding the Adoption of Micro†Generation Technologies: Empirical Evidence for German Homeowners," Working Papers 2015.07, International Network for Economic Research - INFER.
    17. Stefania Troiano & Daniel Vecchiato & Francesco Marangon & Tiziano Tempesta & Federico Nassivera, 2019. "Households’ Preferences for a New ‘Climate-Friendly’ Heating System: Does Contribution to Reducing Greenhouse Gases Matter?," Energies, MDPI, vol. 12(13), pages 1-19, July.
    18. Noeldeke, Beatrice & Winter, Etti & Ntawuhiganayo, Elisée Bahati, 2022. "Representing human decision-making in agent-based simulation models: Agroforestry adoption in rural Rwanda," Ecological Economics, Elsevier, vol. 200(C).
    19. Pothitou, Mary & Hanna, Richard F. & Chalvatzis, Konstantinos J., 2016. "Environmental knowledge, pro-environmental behaviour and energy savings in households: An empirical study," Applied Energy, Elsevier, vol. 184(C), pages 1217-1229.
    20. Houda Elmustapha & Thomas Hoppe & Hans Bressers, 2018. "Understanding Stakeholders’ Views and the Influence of the Socio-Cultural Dimension on the Adoption of Solar Energy Technology in Lebanon," Sustainability, MDPI, vol. 10(2), pages 1-17, January.

    More about this item

    Keywords

    Energy systems model; Agent-based; Residential; CO2;
    All these keywords.

    JEL classification:

    Statistics

    Access and download statistics

    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:eee:energy:v:172:y:2019:i:c:p:752-768. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.