Green Energy and Sustainability ISSN 2771-1641
Green Energy and Sustainability 2026;6(3):0008 | https://doi.org/10.47248/ges2606030008
Original Research Open Access
A comprehensive framework for data management and AI-driven analytics in the energy sector
Alexandros Tsitsanis
,
Fenareti Lampathaki
Correspondence: Alexandros Tsitsanis
Academic Editor(s): Tony Roskilly, Georgios Martinopoulos, Georgia Kastrinaki, Hande Eryilmaz, Martin Roeb
Received: Oct 14, 2025 | Accepted: Jun 29, 2026 | Published: Jul 10, 2026
This article belongs to the Special Issue Selected Papers from the Conference ICRES 2025
Cite this article: Tsitsanis A, Lampathaki F. A comprehensive framework for data management and AI-driven analytics in the energy sector. Green Energy Sustain. 2026;6(3):0008. https://doi.org/10.47248/ges2606030008
The notion of "Energy Data Spaces" is gaining traction as a revolutionary framework within the energy industry, promoting the seamless integration, sharing, and analysis of data among various stakeholders. Endorsed by the European Commission Energy Data Spaces are designed to establish a cohesive digital ecosystem where data from diverse sources, including energy producers, consumers, and grid operators, can be collaboratively leveraged to streamline energy management and boost operational efficiency. This paper delves into the core principles, structural design, and prospective applications of Energy Data Spaces, emphasizing their pivotal role in fostering innovation and sustainability in the energy sector. We present a reference implementation of an Energy Data Space, highlighting the key features that must be addressed, such as data privacy, security, and standardization challenges.
Our findings demonstrate that this framework successfully enables secure, interoperable data exchange across heterogeneous systems, as validated through our collaboration with the Electricity Authority of Cyprus (EAC). The results indicate that providing stakeholders throughout the energy data value chain with an Analytics Catalogue of adaptable AI services significantly optimizes grid operations and demand-side management.
KeywordsEnergy Data Space, AI analytics, energy applications, energy data value, data sharing
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