LAPSE:2023.33765
Published Article
LAPSE:2023.33765
AI and Data Democratisation for Intelligent Energy Management
April 24, 2023
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.
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Keywords
Artificial Intelligence, data democratisation, data sharing, decarbonisation, decision support, energy data spaces, energy management, interoperability
Subject
Suggested Citation
Marinakis V, Koutsellis T, Nikas A, Doukas H. AI and Data Democratisation for Intelligent Energy Management. (2023). LAPSE:2023.33765
Author Affiliations
Marinakis V: School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Zografou (Athens), Greece [ORCID]
Koutsellis T: School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Zografou (Athens), Greece [ORCID]
Nikas A: School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Zografou (Athens), Greece [ORCID]
Doukas H: School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Zografou (Athens), Greece [ORCID]
Koutsellis T: School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Zografou (Athens), Greece [ORCID]
Nikas A: School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Zografou (Athens), Greece [ORCID]
Doukas H: School of Electrical & Computer Engineering, National Technical University of Athens, 15780 Zografou (Athens), Greece [ORCID]
Journal Name
Energies
Volume
14
Issue
14
First Page
4341
Year
2021
Publication Date
2021-07-19
ISSN
1996-1073
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Original Submission
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PII: en14144341, Publication Type: Journal Article
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LAPSE:2023.33765
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https://doi.org/10.3390/en14144341
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Apr 24, 2023
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Apr 24, 2023
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