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Comfort as a Service: A New Paradigm for Residential Environmental Quality Control

Author

Listed:
  • Juan Gómez-Romero

    (Department of Computer Science and Artificial Intelligence, Universidad de Granada, 18071 Granada, Spain)

  • Miguel Molina-Solana

    (Department of Computer Science and Artificial Intelligence, Universidad de Granada, 18071 Granada, Spain)

  • María Ros

    (Department of Computer Science and Artificial Intelligence, Universidad de Granada, 18071 Granada, Spain)

  • M. Dolores Ruiz

    (Department of Computer Science and Artificial Intelligence, Universidad de Granada, 18071 Granada, Spain)

  • M. J. Martin-Bautista

    (Department of Computer Science and Artificial Intelligence, Universidad de Granada, 18071 Granada, Spain)

Abstract

This paper introduces the concept of Comfort as a Service (CaaS), a new energy supply paradigm for providing comfort to residential customers. CaaS takes into account the available passive and active elements, the external factors that affect energy consumption and associated costs, and occupants’ behaviors to generate optimal control strategies for the domestic equipment automatically. As a consequence, it releases building occupants from operating the equipment, which gives rise to a disruption of the traditional model of paying per consumed energy in favor of a model of paying per provided comfort. In the paper, we envision a realization of CaaS based on several technologies such as ambient intelligence, big data, cloud computing and predictive computing. We discuss the opportunities and the barriers of CaaS-centered business and exemplify the potential of CaaS deployments by quantifying the expected energy savings achieved after limiting occupants’ control over the air conditioning system in a test scenario.

Suggested Citation

  • Juan Gómez-Romero & Miguel Molina-Solana & María Ros & M. Dolores Ruiz & M. J. Martin-Bautista, 2018. "Comfort as a Service: A New Paradigm for Residential Environmental Quality Control," Sustainability, MDPI, vol. 10(9), pages 1-15, August.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:9:p:3053-:d:166185
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    References listed on IDEAS

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    4. 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.
    5. Petersen, Steffen & Bundgaard, Katrine Wieck, 2014. "The effect of weather forecast uncertainty on a predictive control concept for building systems operation," Applied Energy, Elsevier, vol. 116(C), pages 311-321.
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    Cited by:

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    3. Mahendra Singh & Jiao Jiao & Marian Klobasa & Rainer Frietsch, 2022. "Servitization of Energy Sector: Emerging Service Business Models and Startup’s Participation," Energies, MDPI, vol. 15(7), pages 1-20, April.

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