IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v49y2012icp149-153.html

Open source software and crowdsourcing for energy analysis

Author

Listed:
  • Bazilian, Morgan
  • Rice, Andrew
  • Rotich, Juliana
  • Howells, Mark
  • DeCarolis, Joseph
  • Macmillan, Stuart
  • Brooks, Cameron
  • Bauer, Florian
  • Liebreich, Michael

Abstract

Informed energy decision making requires effective software, high-quality input data, and a suitably trained user community. Developing these resources can be expensive and time consuming. Even when data and tools are intended for public re-use they often come with technical, legal, economic and social barriers that make them difficult to adopt, adapt and combine for use in new contexts. We focus on the promise of open, publically accessible software and data as well as crowdsourcing techniques to develop robust energy analysis tools that can deliver crucial, policy-relevant insight, particularly in developing countries, where planning resources are highly constrained—and the need to adapt these resources and methods to the local context is high. We survey existing research, which argues that these techniques can produce high-quality results, and also explore the potential role that linked, open data can play in both supporting the modelling process and in enhancing public engagement with energy issues.

Suggested Citation

  • Bazilian, Morgan & Rice, Andrew & Rotich, Juliana & Howells, Mark & DeCarolis, Joseph & Macmillan, Stuart & Brooks, Cameron & Bauer, Florian & Liebreich, Michael, 2012. "Open source software and crowdsourcing for energy analysis," Energy Policy, Elsevier, vol. 49(C), pages 149-153.
    • Handle: RePEc:eee:enepol:v:49:y:2012:i:c:p:149-153
    DOI: 10.1016/j.enpol.2012.06.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421512005423
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2012.06.032?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Paolacci, Gabriele & Chandler, Jesse & Ipeirotis, Panagiotis G., 2010. "Running experiments on Amazon Mechanical Turk," Judgment and Decision Making, Cambridge University Press, vol. 5(5), pages 411-419, August.
    2. Bitzer, Jurgen, 2004. "Commercial versus open source software: the role of product heterogeneity in competition," Economic Systems, Elsevier, vol. 28(4), pages 369-381, December.
    3. Gabriele Paolacci & Jesse Chandler & Panagiotis G. Ipeirotis, 2010. "Running experiments on Amazon Mechanical Turk," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 5(5), pages 411-419, August.
    4. Howells, Mark & Rogner, Holger & Strachan, Neil & Heaps, Charles & Huntington, Hillard & Kypreos, Socrates & Hughes, Alison & Silveira, Semida & DeCarolis, Joe & Bazillian, Morgan & Roehrl, Alexander, 2011. "OSeMOSYS: The Open Source Energy Modeling System: An introduction to its ethos, structure and development," Energy Policy, Elsevier, vol. 39(10), pages 5850-5870, October.
    5. Bazilian, Morgan & Sagar, Ambuj & Detchon, Reid & Yumkella, Kandeh, 2010. "More heat and light," Energy Policy, Elsevier, vol. 38(10), pages 5409-5412, October.
    6. Johnson, Justin P., 2006. "Collaboration, peer review and open source software," Information Economics and Policy, Elsevier, vol. 18(4), pages 477-497, November.
    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. Groissböck, Markus & Pickl, Matthias J., 2018. "Fuel-price reform to achieve climate and energy policy goals in Saudi Arabia: A multiple-scenario analysis," Utilities Policy, Elsevier, vol. 50(C), pages 1-12.
    2. Sacha Hodencq & Mathieu Brugeron & Jaume Fitó & Lou Morriet & Benoit Delinchant & Frédéric Wurtz, 2021. "OMEGAlpes, an Open-Source Optimisation Model Generation Tool to Support Energy Stakeholders at District Scale," Energies, MDPI, vol. 14(18), pages 1-30, September.
    3. Bistline, John E.T. & Merrick, James H., 2020. "Parameterizing open-source energy models: Statistical learning to estimate unknown power plant attributes," Applied Energy, Elsevier, vol. 269(C).
    4. Dall-Orsoletta, Alaize & Romero, Fernando & Ferreira, Paula, 2022. "Open and collaborative innovation for the energy transition: An exploratory study," Technology in Society, Elsevier, vol. 69(C).
    5. Fleischhacker, Andreas & Lettner, Georg & Schwabeneder, Daniel & Auer, Hans, 2019. "Portfolio optimization of energy communities to meet reductions in costs and emissions," Energy, Elsevier, vol. 173(C), pages 1092-1105.
    6. Bale, Catherine S.E. & Varga, Liz & Foxon, Timothy J., 2015. "Energy and complexity: New ways forward," Applied Energy, Elsevier, vol. 138(C), pages 150-159.
    7. Zwickl-Bernhard, Sebastian & Auer, Hans, 2021. "Open-source modeling of a low-carbon urban neighborhood with high shares of local renewable generation," Applied Energy, Elsevier, vol. 282(PA).
    8. Onyeji-Nwogu, Ijeoma & Bazilian, Morgan & Moss, Todd, 2020. "Big data and the electricity sector in African countries," World Development Perspectives, Elsevier, vol. 17(C).
    9. Hall, Lisa M.H. & Buckley, Alastair R., 2016. "A review of energy systems models in the UK: Prevalent usage and categorisation," Applied Energy, Elsevier, vol. 169(C), pages 607-628.
    10. Groissböck, Markus, 2019. "Are open source energy system optimization tools mature enough for serious use?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 234-248.
    11. Staffell, Iain & Pfenninger, Stefan, 2018. "The increasing impact of weather on electricity supply and demand," Energy, Elsevier, vol. 145(C), pages 65-78.
    12. Jonathan Klimt & Niklas Eiling & Felix Wege & Jonas Baude & Antonello Monti, 2023. "The Role of Open-Source Software in the Energy Sector," Energies, MDPI, vol. 16(16), pages 1-17, August.
    13. 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).
    14. Rady, Yassin Yehia & Rocco, Matteo V. & Serag-Eldin, M.A. & Colombo, Emanuela, 2018. "Modelling for power generation sector in Developing Countries: Case of Egypt," Energy, Elsevier, vol. 165(PB), pages 198-209.
    15. Dhakouani, Asma & Znouda, Essia & Bouden, Chiheb, 2019. "Impacts of energy efficiency policies on the integration of renewable energy," Energy Policy, Elsevier, vol. 133(C).
    16. Jens Weibezahn & Mario Kendziorski, 2019. "Illustrating the Benefits of Openness: A Large-Scale Spatial Economic Dispatch Model Using the Julia Language," Energies, MDPI, vol. 12(6), pages 1-21, March.

    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. Engelhardt, Sebastian v. & Freytag, Andreas, 2013. "Institutions, culture, and open source," Journal of Economic Behavior & Organization, Elsevier, vol. 95(C), pages 90-110.
    2. Sweldens, Steven & Puntoni, Stefano & Paolacci, Gabriele & Vissers, Maarten, 2014. "The bias in the bias: Comparative optimism as a function of event social undesirability," Organizational Behavior and Human Decision Processes, Elsevier, vol. 124(2), pages 229-244.
    3. Hsu, Dan K. & Burmeister-Lamp, Katrin & Simmons, Sharon A. & Foo, Maw-Der & Hong, Michelle C. & Pipes, Jesse D., 2019. "“I know I can, but I don't fit”: Perceived fit, self-efficacy, and entrepreneurial intention," Journal of Business Venturing, Elsevier, vol. 34(2), pages 311-326.
    4. Lutz, Christoph & Newlands, Gemma, 2018. "Consumer segmentation within the sharing economy: The case of Airbnb," Journal of Business Research, Elsevier, vol. 88(C), pages 187-196.
    5. Mariconda, Simone & Lurati, Francesco, 2015. "Does familiarity breed stability? The role of familiarity in moderating the effects of new information on reputation judgments," Journal of Business Research, Elsevier, vol. 68(5), pages 957-964.
    6. Tobias Schlager & Ashley V. Whillans, 2022. "People underestimate the probability of contracting the coronavirus from friends," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.
    7. Hou, Chenxuan & Li, Tingting & Gu, Yanzhang, 2026. "Artificial intelligence versus human providers for personalized solutions? The influence of expected group size and perceived uniqueness on adoption intentions," Journal of Retailing and Consumer Services, Elsevier, vol. 88(C).
    8. Charness, Gary & Gneezy, Uri & Kuhn, Michael A., 2013. "Experimental methods: Extra-laboratory experiments-extending the reach of experimental economics," Journal of Economic Behavior & Organization, Elsevier, vol. 91(C), pages 93-100.
    9. Orazi, Davide C. & Pizzetti, Marta, 2015. "Revisiting fear appeals: A structural re-inquiry of the protection motivation model," International Journal of Research in Marketing, Elsevier, vol. 32(2), pages 223-225.
    10. Cantarella, Michele & Strozzi, Chiara, 2019. "Workers in the Crowd: The Labour Market Impact of the Online Platform Economy," IZA Discussion Papers 12327, IZA Network @ LISER.
    11. Gökçe Esenduran & James A. Hill & In Joon Noh, 2020. "Understanding the Choice of Online Resale Channel for Used Electronics," Production and Operations Management, Production and Operations Management Society, vol. 29(5), pages 1188-1211, May.
    12. Azzam, Tarek & Harman, Elena, 2016. "Crowdsourcing for quantifying transcripts: An exploratory study," Evaluation and Program Planning, Elsevier, vol. 54(C), pages 63-73.
    13. Gonzalez-Cabello, Martin & Siddiq, Auyon & Corbett, Charles J. & Hu, Catherine, 2025. "Fairness in crowdwork: Making the human AI supply chain more humane," Business Horizons, Elsevier, vol. 68(5), pages 645-657.
    14. Gandullia, Luca & Lezzi, Emanuela & Parciasepe, Paolo, 2020. "Replication with MTurk of the experimental design by Gangadharan, Grossman, Jones & Leister (2018): Charitable giving across donor types," Journal of Economic Psychology, Elsevier, vol. 78(C).
    15. Prissé, Benjamin & Jorrat, Diego, 2022. "Lab vs online experiments: No differences," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 100(C).
    16. Efrat Dressler & Yevgeny Mugerman, 2023. "Doing the Right Thing? The Voting Power Effect and Institutional Shareholder Voting," Journal of Business Ethics, Springer, vol. 183(4), pages 1089-1112, April.
    17. Valerio Capraro & Hélène Barcelo, 2021. "Punishing defectors and rewarding cooperators: Do people discriminate between genders?," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 7(1), pages 19-32, September.
    18. Farooq, Ali & Salminen, Joni & Dahabiyeh, Laila & Javed, Yousra & Jansen, Bernard J., 2026. "Does negative buzz result in social media discontinuation? Investigating the effects of negative word of mouth in the United States, India, and Finland," Technology in Society, Elsevier, vol. 84(C).
    19. Gupta, Vishal K. & Goktan, A. Banu & Gunay, Gonca, 2014. "Gender differences in evaluation of new business opportunity: A stereotype threat perspective," Journal of Business Venturing, Elsevier, vol. 29(2), pages 273-288.
    20. Garbarino, Ellen & Slonim, Robert & Villeval, Marie Claire, 2019. "Loss aversion and lying behavior," Journal of Economic Behavior & Organization, Elsevier, vol. 158(C), pages 379-393.

    More about this item

    Keywords

    ;
    ;
    ;

    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:enepol:v:49:y:2012:i:c:p:149-153. 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.