IDEAS home Printed from https://ideas.repec.org/a/eee/juipol/v53y2018icp73-83.html
   My bibliography  Save this article

Understanding the future of Seawater Air Conditioning in the Caribbean: A simulation approach

Author

Listed:
  • Arias-Gaviria, Jessica
  • Larsen, Erik R.
  • Arango-Aramburo, Santiago

Abstract

Seawater Air Conditioning (SWAC) is a sustainable alternative for tropical islands. Despite its potential, adoption has been limited throughout the world. There is a need to understand SWAC adoption potential in the Caribbean and to identify the actions and policies that could favor its diffusion. We develop a system dynamics simulation model for SWAC adoption, and use it to simulate scenarios and incentives for SWAC in Jamaica. We found that SWAC adoption is mainly limited by the threshold capacity necessary for the first installation. To achieve full adoption by 2050, governments and investors should finance 100% of the first pipeline before 2020.

Suggested Citation

  • Arias-Gaviria, Jessica & Larsen, Erik R. & Arango-Aramburo, Santiago, 2018. "Understanding the future of Seawater Air Conditioning in the Caribbean: A simulation approach," Utilities Policy, Elsevier, vol. 53(C), pages 73-83.
    • Handle: RePEc:eee:juipol:v:53:y:2018:i:c:p:73-83
    DOI: 10.1016/j.jup.2018.06.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0957178718300420
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jup.2018.06.008?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. Kleijnen, Jack P. C., 1995. "Verification and validation of simulation models," European Journal of Operational Research, Elsevier, vol. 82(1), pages 145-162, April.
    2. Jeroen Struben & John D Sterman, 2008. "Transition Challenges for Alternative Fuel Vehicle and Transportation Systems," Environment and Planning B, , vol. 35(6), pages 1070-1097, December.
    3. Alishahi, E. & Moghaddam, M. Parsa & Sheikh-El-Eslami, M.K., 2012. "A system dynamics approach for investigating impacts of incentive mechanisms on wind power investment," Renewable Energy, Elsevier, vol. 37(1), pages 310-317.
    4. Daniel McFadden, 2001. "Economic Choices," American Economic Review, American Economic Association, vol. 91(3), pages 351-378, June.
    5. Haas, Reinhard & Resch, Gustav & Panzer, Christian & Busch, Sebastian & Ragwitz, Mario & Held, Anne, 2011. "Efficiency and effectiveness of promotion systems for electricity generation from renewable energy sources – Lessons from EU countries," Energy, Elsevier, vol. 36(4), pages 2186-2193.
    6. Ferioli, F. & Schoots, K. & van der Zwaan, B.C.C., 2009. "Use and limitations of learning curves for energy technology policy: A component-learning hypothesis," Energy Policy, Elsevier, vol. 37(7), pages 2525-2535, July.
    7. Geller, Howard & Harrington, Philip & Rosenfeld, Arthur H. & Tanishima, Satoshi & Unander, Fridtjof, 2006. "Polices for increasing energy efficiency: Thirty years of experience in OECD countries," Energy Policy, Elsevier, vol. 34(5), pages 556-573, March.
    8. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    9. Edwards, Erwin Elliot & Iyare, O.S. & Moseley, L.L., 2012. "Energy consumption in typical Caribbean office buildings: A potential short term solution to energy concerns," Renewable Energy, Elsevier, vol. 39(1), pages 154-161.
    10. 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.
    11. Eppstein, Margaret J. & Grover, David K. & Marshall, Jeffrey S. & Rizzo, Donna M., 2011. "An agent-based model to study market penetration of plug-in hybrid electric vehicles," Energy Policy, Elsevier, vol. 39(6), pages 3789-3802, June.
    12. Massiani, Jérôme & Gohs, Andreas, 2015. "The choice of Bass model coefficients to forecast diffusion for innovative products: An empirical investigation for new automotive technologies," Research in Transportation Economics, Elsevier, vol. 50(C), pages 17-28.
    13. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    14. Osorio, Andrés F. & Arias-Gaviria, Jessica & Devis-Morales, Andrea & Acevedo, Diego & Velasquez, Héctor Iván & Arango-Aramburo, Santiago, 2016. "Beyond electricity: The potential of ocean thermal energy and ocean technology ecoparks in small tropical islands," Energy Policy, Elsevier, vol. 98(C), pages 713-724.
    15. 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.
    16. Toka, Agorasti & Iakovou, Eleftherios & Vlachos, Dimitrios & Tsolakis, Naoum & Grigoriadou, Anastasia-Loukia, 2014. "Managing the diffusion of biomass in the residential energy sector: An illustrative real-world case study," Applied Energy, Elsevier, vol. 129(C), pages 56-69.
    17. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    18. Chua, K.J. & Chou, S.K. & Yang, W.M. & Yan, J., 2013. "Achieving better energy-efficient air conditioning – A review of technologies and strategies," Applied Energy, Elsevier, vol. 104(C), pages 87-104.
    19. Jamasb, T. & Köhler, J., 2007. "Learning Curves For Energy Technology and Policy Analysis: A Critical Assessment," Cambridge Working Papers in Economics 0752, Faculty of Economics, University of Cambridge.
    20. Pelc, Robin & Fujita, Rod M., 2002. "Renewable energy from the ocean," Marine Policy, Elsevier, vol. 26(6), pages 471-479, November.
    21. Jeroen Struben & John D. Sterman, 2008. "Transition Challenges for Alternative Fuel Vehicle and Transportation Systems," Post-Print hal-02312277, HAL.
    22. Gary, Shayne & Larsen, Erik Reimer, 2000. "Improving firm performance in out-of-equilibrium, deregulated markets using feedback simulation models," Energy Policy, Elsevier, vol. 28(12), pages 845-855, October.
    23. Lo, Kevin, 2014. "A critical review of China's rapidly developing renewable energy and energy efficiency policies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 508-516.
    24. Lund, Peter, 2006. "Market penetration rates of new energy technologies," Energy Policy, Elsevier, vol. 34(17), pages 3317-3326, November.
    25. Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
    26. Rao, K. Usha & Kishore, V.V.N., 2010. "A review of technology diffusion models with special reference to renewable energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1070-1078, April.
    27. Ren, Zhengen & Paevere, Phillip & Grozev, George & Egan, Stephen & Anticev, Julia, 2013. "Assessment of end-use electricity consumption and peak demand by Townsville's housing stock," Energy Policy, Elsevier, vol. 61(C), pages 888-893.
    28. Michael Pidd, 1999. "Just Modeling Through: A Rough Guide to Modeling," Interfaces, INFORMS, vol. 29(2), pages 118-132, April.
    29. Popp, David & Hascic, Ivan & Medhi, Neelakshi, 2011. "Technology and the diffusion of renewable energy," Energy Economics, Elsevier, vol. 33(4), pages 648-662, July.
    30. Purohit, Pallav & Kandpal, Tara C., 2005. "Renewable energy technologies for irrigation water pumping in India: projected levels of dissemination, energy delivery and investment requirements using available diffusion models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 9(6), pages 592-607, December.
    31. Arias-Gaviria, Jessica & van der Zwaan, Bob & Kober, Tom & Arango-Aramburo, Santiago, 2017. "The prospects for Small Hydropower in Colombia," Renewable Energy, Elsevier, vol. 107(C), pages 204-214.
    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. Milad Shadman & Mateo Roldan-Carvajal & Fabian G. Pierart & Pablo Alejandro Haim & Rodrigo Alonso & Corbiniano Silva & Andrés F. Osorio & Nathalie Almonacid & Griselda Carreras & Mojtaba Maali Amiri &, 2023. "A Review of Offshore Renewable Energy in South America: Current Status and Future Perspectives," Sustainability, MDPI, vol. 15(2), pages 1-34, January.
    2. Xin-gang, Zhao & Wei, Wang & Jieying, Wang, 2022. "The policy effects of demand-pull and technology-push on the diffusion of wind power: A scenario analysis based on system dynamics approach," Energy, Elsevier, vol. 261(PA).

    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. Arias-Gaviria, Jessica & Carvajal-Quintero, Sandra Ximena & Arango-Aramburo, Santiago, 2019. "Understanding dynamics and policy for renewable energy diffusion in Colombia," Renewable Energy, Elsevier, vol. 139(C), pages 1111-1119.
    2. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
    3. Hidayatno, Akhmad & Jafino, Bramka Arga & Setiawan, Andri D. & Purwanto, Widodo Wahyu, 2020. "When and why does transition fail? A model-based identification of adoption barriers and policy vulnerabilities for transition to natural gas vehicles," Energy Policy, Elsevier, vol. 138(C).
    4. Brito, Thiago Luis Felipe & Islam, Towhidul & Stettler, Marc & Mouette, Dominique & Meade, Nigel & Moutinho dos Santos, Edmilson, 2019. "Transitions between technological generations of alternative fuel vehicles in Brazil," Energy Policy, Elsevier, vol. 134(C).
    5. Tran, Martino, 2012. "Technology-behavioural modelling of energy innovation diffusion in the UK," Applied Energy, Elsevier, vol. 95(C), pages 1-11.
    6. Marc Baudry & Clément Bonnet, 2019. "Demand-Pull Instruments and the Development of Wind Power in Europe: A Counterfactual Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(2), pages 385-429, June.
    7. Montoya-Duque, Laura & Arango-Aramburo, Santiago & Arias-Gaviria, Jessica, 2022. "Simulating the effect of the Pay-as-you-go scheme for solar energy diffusion in Colombian off-grid regions," Energy, Elsevier, vol. 244(PB).
    8. Hesselink, Laurens X.W. & Chappin, Emile J.L., 2019. "Adoption of energy efficient technologies by households – Barriers, policies and agent-based modelling studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 99(C), pages 29-41.
    9. Marc Baudry & Clément Bonnet, 2016. "Demand pull isntruments and the development of wind power in Europe: A counter-factual analysis," Working Papers 1607, Chaire Economie du climat.
    10. Scheller, Fabian & Johanning, Simon & Bruckner, Thomas, 2019. "A review of designing empirically grounded agent-based models of innovation diffusion: Development process, conceptual foundation and research agenda," Contributions of the Institute for Infrastructure and Resources Management 01/2019, University of Leipzig, Institute for Infrastructure and Resources Management.
    11. Santhakumar, Srinivasan & Meerman, Hans & Faaij, André, 2021. "Improving the analytical framework for quantifying technological progress in energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    12. Zhang, Qi & Li, Hailong & Zhu, Lijing & Campana, Pietro Elia & Lu, Huihui & Wallin, Fredrik & Sun, Qie, 2018. "Factors influencing the economics of public charging infrastructures for EV – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 500-509.
    13. Toka, Agorasti & Iakovou, Eleftherios & Vlachos, Dimitrios & Tsolakis, Naoum & Grigoriadou, Anastasia-Loukia, 2014. "Managing the diffusion of biomass in the residential energy sector: An illustrative real-world case study," Applied Energy, Elsevier, vol. 129(C), pages 56-69.
    14. Lee, Chul-Yong & Huh, Sung-Yoon, 2017. "Forecasting the diffusion of renewable electricity considering the impact of policy and oil prices: The case of South Korea," Applied Energy, Elsevier, vol. 197(C), pages 29-39.
    15. Rao, K. Usha & Kishore, V.V.N., 2010. "A review of technology diffusion models with special reference to renewable energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1070-1078, April.
    16. Scheller, Fabian & Johanning, Simon & Bruckner, Thomas, 2018. "IRPsim: A techno-socio-economic energy system model vision for business strategy assessment at municipal level," Contributions of the Institute for Infrastructure and Resources Management 02/2018, University of Leipzig, Institute for Infrastructure and Resources Management.
    17. Huh, Sung-Yoon & Lee, Chul-Yong, 2014. "Diffusion of renewable energy technologies in South Korea on incorporating their competitive interrelationships," Energy Policy, Elsevier, vol. 69(C), pages 248-257.
    18. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    19. Liu, Xueying & Madlener, Reinhard, 2019. "Get Ready for Take-Off: A Two-Stage Model of Aircraft Market Diffusion," FCN Working Papers 15/2019, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    20. Zhang, Cen & Schmöcker, Jan-Dirk & Kuwahara, Masahiro & Nakamura, Toshiyuki & Uno, Nobuhiro, 2020. "A diffusion model for estimating adoption patterns of a one-way carsharing system in its initial years," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 135-150.

    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:juipol:v:53:y:2018:i:c:p:73-83. 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: https://www.sciencedirect.com/journal/utilities-policy .

    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.