[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v38y2010i6p2763-2775.html
   My bibliography  Save this article

Exploring domestic micro-cogeneration in the Netherlands: An agent-based demand model for technology diffusion

Author

Listed:
  • Faber, Albert
  • Valente, Marco
  • Janssen, Peter
Abstract
Micro-cogeneration (micro-CHP) is a new technology at the household level, producing electricity in cogeneration with domestic heating, thereby increasing the overall efficiency of domestic energy production. We have developed a prototypical agent-based simulation model for energy technologies competing for demand at the consumer level. The model is specifically geared towards the competition between micro-CHP and incumbent condensing boilers. In the model, both technologies compete on purchase price and costs of usage, to which various (types of) consumers decide on the installation of either technology. Simulations with various gas and electricity prices show that micro-CHP diffusion could be seriously inhibited if demand for natural gas decreases, e.g. due to insulation measures. Further simulations explore various subsidy schemes. A subsidy for purchase is only found to be effective within a limited range of [euro]1400-3250. A subsidy based on decreasing price difference between the competing technologies is much more cost effective than fixed purchase subsidies. Simulations of a subsidy scheme for usage show that a fast market penetration can be reached, but this does not yet take full advantage of technological progress in terms of decreasing CO2 emissions. Selection of the most effective scheme thus depends on the policy criteria assumed.

Suggested Citation

  • Faber, Albert & Valente, Marco & Janssen, Peter, 2010. "Exploring domestic micro-cogeneration in the Netherlands: An agent-based demand model for technology diffusion," Energy Policy, Elsevier, vol. 38(6), pages 2763-2775, June.
    • Handle: RePEc:eee:enepol:v:38:y:2010:i:6:p:2763-2775
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301-4215(10)00014-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Paul Windrum & Giorgio Fagiolo & Alessio Moneta, 2007. "Empirical Validation of Agent-Based Models: Alternatives and Prospects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-8.
    2. Pan, Haoran & Kohler, Jonathan, 2007. "Technological change in energy systems: Learning curves, logistic curves and input-output coefficients," Ecological Economics, Elsevier, vol. 63(4), pages 749-758, September.
    3. Sauter, Raphael & Watson, Jim, 2007. "Strategies for the deployment of micro-generation: Implications for social acceptance," Energy Policy, Elsevier, vol. 35(5), pages 2770-2779, May.
    4. Marco Valente, 2008. "Laboratory for Simulation Develpment - LSD," LEM Papers Series 2008/12, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Dennis E. Smallwood & John Conlisk, 1979. "Product Quality in Markets Where Consumers are Imperfectly Informed," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 93(1), pages 1-23.
    6. J. Stanley Metcalfe & John Foster (ed.), 2004. "Evolution and Economic Complexity," Books, Edward Elgar Publishing, number 3216.
    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. Francesco Pasimeni, 2017. "Adoption and Diffusion of Micro-Grids in Italy. An Analysis of Regional Factors Using Agent-Based Modelling," SPRU Working Paper Series 2017-09, SPRU - Science Policy Research Unit, University of Sussex Business School.
    2. Vandin, Andrea & Giachini, Daniele & Lamperti, Francesco & Chiaromonte, Francesca, 2022. "Automated and distributed statistical analysis of economic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    3. Marco Valente, 2009. "Markets fo Heterogeneous Products: a Boundedly Rational Consumer Model," LEM Papers Series 2009/11, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    4. Marcelo De Carvalho Pereira, 2014. "When Competition May Hinder Technologydiffusion: The Case Of Internet Access Services In Brazil," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 152, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    5. Francesco Pasimeni & Tommaso Ciarli, 2018. "Diffusion of Shared Goods in Consumer Coalitions. An Agent-Based Model," SPRU Working Paper Series 2018-24, SPRU - Science Policy Research Unit, University of Sussex Business School.
    6. Qian, Yuan & Scherer, Laura & Tukker, Arnold & Behrens, Paul, 2020. "China's potential SO2 emissions from coal by 2050," Energy Policy, Elsevier, vol. 147(C).
    7. Ron Boschma & Ron Martin, 2010. "The Aims and Scope of Evolutionary Economic Geography," Chapters, in: Ron Boschma & Ron Martin (ed.), The Handbook of Evolutionary Economic Geography, chapter 1, Edward Elgar Publishing.
    8. LeBaron Blake & Winker Peter, 2008. "Introduction to the Special Issue on Agent-Based Models for Economic Policy Advice," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 141-148, April.
    9. Arnaud Z. Dragicevic, 2019. "Market Coordination Under Non-Equilibrium Dynamics," Networks and Spatial Economics, Springer, vol. 19(3), pages 697-715, September.
    10. Polzin, Friedemann & Sanders, Mark & Serebriakova, Alexandra, 2021. "Finance in global transition scenarios: Mapping investments by technology into finance needs by source," Energy Economics, Elsevier, vol. 99(C).
    11. Corrado Monti & Marco Pangallo & Gianmarco De Francisci Morales & Francesco Bonchi, 2022. "On learning agent-based models from data," Papers 2205.05052, arXiv.org, revised Nov 2022.
    12. Lovering, Jessica R. & Yip, Arthur & Nordhaus, Ted, 2016. "Historical construction costs of global nuclear power reactors," Energy Policy, Elsevier, vol. 91(C), pages 371-382.
    13. Lamperti, Francesco & Roventini, Andrea & Sani, Amir, 2018. "Agent-based model calibration using machine learning surrogates," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 366-389.
    14. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    15. repec:hal:spmain:info:hdl:2441/f6h8764enu2lskk9p4oq2cqb0 is not listed on IDEAS
    16. Nadia Fiorino & Emma Galli & Ilde Rizzo & Marco Valente, 2023. "Public procurement and reputation. An agent‐based model," Metroeconomica, Wiley Blackwell, vol. 74(4), pages 806-832, November.
    17. André Lorentz & Tommaso Ciarli & Maria Savona & Marco Valente, 2016. "The effect of demand-driven structural transformations on growth and technological change," Journal of Evolutionary Economics, Springer, vol. 26(1), pages 219-246, March.
    18. Gomes, Sharlene L. & Hermans, Leon M. & Thissen, Wil A.H., 2018. "Extending community operational research to address institutional aspects of societal problems: Experiences from peri-urban Bangladesh," European Journal of Operational Research, Elsevier, vol. 268(3), pages 904-917.
    19. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.
    20. John DiNardo & David S. Lee, 2010. "Program Evaluation and Research Designs," Working Papers 1228, Princeton University, Department of Economics, Industrial Relations Section..
    21. Mattia Guerini & Francesco Lamperti & Mauro Napoletano & Andrea Roventini & Tania Treibich, 2022. "Unconventional monetary policies in an agent-based model with mark-to-market standards," Review of Evolutionary Political Economy, Springer, vol. 3(1), pages 73-107, April.

    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:enepol:v:38:y:2010:i:6:p:2763-2775. 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.elsevier.com/locate/enpol .

    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.