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AI and Data Democratisation for Intelligent Energy Management

Author

Listed:
  • Vangelis Marinakis

    (School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Zografou (Athens), Greece)

  • Themistoklis Koutsellis

    (School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Zografou (Athens), Greece)

  • Alexandros Nikas

    (School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Zografou (Athens), Greece)

  • Haris Doukas

    (School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Zografou (Athens), Greece)

Abstract

Despite the large number of technology-intensive organisations, their corporate know-how and underlying workforce skill are not mature enough for a successful rollout of Artificial Intelligence (AI) services in the near-term. However, things have started to change, owing to the increased adoption of data democratisation processes, and the capability offered by emerging technologies for data sharing while respecting privacy, protection, and security, as well as appropriate learning-based modelling capabilities for non-expert end-users. This is particularly evident in the energy sector. In this context, the aim of this paper is to analyse AI and data democratisation, in order to explore the strengths and challenges in terms of data access problems and data sharing, algorithmic bias, AI transparency, privacy and other regulatory constraints for AI-based decisions, as well as novel applications in different domains, giving particular emphasis on the energy sector. A data democratisation framework for intelligent energy management is presented. In doing so, it highlights the need for the democratisation of data and analytics in the energy sector, toward making data available for the right people at the right time, allowing them to make the right decisions, and eventually facilitating the adoption of decentralised, decarbonised, and democratised energy business models.

Suggested Citation

  • Vangelis Marinakis & Themistoklis Koutsellis & Alexandros Nikas & Haris Doukas, 2021. "AI and Data Democratisation for Intelligent Energy Management," Energies, MDPI, vol. 14(14), pages 1-14, July.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:14:p:4341-:d:596969
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    References listed on IDEAS

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    1. Pfenninger, Stefan & Hirth, Lion & Schlecht, Ingmar & Schmid, Eva & Wiese, Frauke & Brown, Tom & Davis, Chris & Gidden, Matthew & Heinrichs, Heidi & Heuberger, Clara & Hilpert, Simon & Krien, Uwe & Ma, 2018. "Opening the black box of energy modelling: Strategies and lessons learned," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 19, pages 63-71.
    2. Doukas, Haris & Nikas, Alexandros, 2020. "Decision support models in climate policy," European Journal of Operational Research, Elsevier, vol. 280(1), pages 1-24.
    3. Yueqiang Xu & Petri Ahokangas & Jean-Nicolas Louis & Eva Pongrácz, 2019. "Electricity Market Empowered by Artificial Intelligence: A Platform Approach," Energies, MDPI, vol. 12(21), pages 1-21, October.
    4. Vangelis Marinakis, 2020. "Big Data for Energy Management and Energy-Efficient Buildings," Energies, MDPI, vol. 13(7), pages 1-18, March.
    5. Haris Doukas & Alexandros Nikas, 2021. "Involve citizens in climate-policy modelling," Nature, Nature, vol. 590(7846), pages 389-389, February.
    6. David L. Olson & Dursun Delen, 2008. "Advanced Data Mining Techniques," Springer Books, Springer, number 978-3-540-76917-0, July.
    7. Nikas, A. & Gambhir, A. & Trutnevyte, E. & Koasidis, K. & Lund, H. & Thellufsen, J.Z. & Mayer, D. & Zachmann, G. & Miguel, L.J. & Ferreras-Alonso, N. & Sognnaes, I. & Peters, G.P. & Colombo, E. & Howe, 2021. "Perspective of comprehensive and comprehensible multi-model energy and climate science in Europe," Energy, Elsevier, vol. 215(PA).
    8. Gupta, Shivam & Chen, Haozhe & Hazen, Benjamin T. & Kaur, Sarabjot & Santibañez Gonzalez, Ernesto D.R., 2019. "Circular economy and big data analytics: A stakeholder perspective," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 466-474.
    9. Daniel Jato-Espino & Carmen Ruiz-Puente, 2020. "Fostering Circular Economy Through the Analysis of Existing Open Access Industrial Symbiosis Databases," Sustainability, MDPI, vol. 12(3), pages 1-24, January.
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    Cited by:

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