Big Data Reference Architecture for the Energy Sector
Sustainability, vol. 17, pp. 6488
Abstract
Data sharing within and across large, complex systems is one of the most topical challenges in the current IT landscape, and the energy domain is no exception. As the sector becomes more and more digitized, decentralized, and complex, new Big Data and AI tools are constantly emerging to empower stakeholders to exploit opportunities and tackle challenges. They enable advancements such as the efficient operation and maintenance of assets, forecasting of demand and production, and improved decision-making. However, in turn, innovative systems are necessary for using and operating such tools, as they often require large amounts of disparate data and intelligent preprocessing. The integration of and communication between numerous up-and-coming technologies is necessary to ensure the maximum exploitation of renewable energy. Building on existing developments and initiatives, this paper introduces a multi-layer Reference Architecture for the reliable, secure, and trusted exchange of data and facilitation of services within the energy domain.
Authors 4
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Fraunhofer Institute for Applied Information Technology · RWTH Aachen University
Affiliation as printed
Digital Energy, Fraunhofer FIT, 52068 Aachen, Germany
Institute for Automation of Complex Power Systems, RWTH Aachen, 52074 Aachen, Germany
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Affiliation as printed
Institute for Automation of Complex Power Systems, RWTH Aachen, 52074 Aachen, Germany
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Affiliation as printed
Institute for Automation of Complex Power Systems, RWTH Aachen, 52074 Aachen, Germany
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Fraunhofer Institute for Applied Information Technology · RWTH Aachen University
Affiliation as printed
Digital Energy, Fraunhofer FIT, 52068 Aachen, Germany
Institute for Automation of Complex Power Systems, RWTH Aachen, 52074 Aachen, Germany
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