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Topic Taxonomy and Metadata to Support Renewable Energy Digitalisation

Author

Listed:
  • Andrea Michiorri

    (Mines Paris, PSL University, Centre for Processes, Renewable Energy and Energy Systems (PERSEE), 06904 Sophia Antipolis, France)

  • Anna Maria Sempreviva

    (Department of Wind Energy and Energy Systems, Technical University of Denmark, DTU, Risoe Campus, Frederiksborgvej 399, 4000 Roskilde, Denmark)

  • Sean Philipp

    (AIT Austrian Institute of Technology GmbH, Giefinggasse 2, 1210 Vienna, Austria)

  • Paula Perez-Lopez

    (Mines Paris, PSL University, Centre Observation, Impacts, Energy (O.I.E.), 06904 Sophia Antipolis, France)

  • Alain Ferriere

    (Laboratoire PROMES-CNRS, 7 Rue Du Four Solaire, 66120 Font-Romeu Odeillo, France)

  • David Moser

    (EURAC Research, Viale Druso, 1, 39100 Bolzano, Italy)

Abstract

Research and innovation in renewable energy, such as wind and solar, have been supporting the green transformation of energy systems, the backbone of a low-carbon climate-resilient society. The major challenge is to manage the complexity of the grid transformation to allow for higher shares of highly variable renewables while securing the safety of the stability of the grid and a stable energy supply. A great help comes from the ongoing digital transformation where digitisation of infrastructures and assets in research and industry generates multi-dimensional and multi-disciplinary digital data. However, a data user needs help to find the correct data to exploit. This has two significant facets: first, missing data management, i.e., datasets are neither findable because of missing community standard metadata and taxonomies, nor interoperable, i.e., missing standards for data formats; second, data owners having a negative perception of sharing data. To make data ready for data science exploitation, one of the necessary steps to map the existing data and their availability to facilitate their access is to create a taxonomy for the field’s topics. For this, a group of experts in different renewable technologies such as photovoltaics, wind and concentrated solar power and in transversal fields such as life cycle assessment and the EU taxonomy for sustainable activities have been gathered to propose a coherent and detailed taxonomy for renewable energy-related data. The result is a coherent classification of relevant data sources, considering both the general aspects applicable to electricity generation from selected renewable energy technologies and the specific aspects of each of them. It is based on previous relevant work and can be easily extended to other renewable resources not considered in this work and conventional energy technology.

Suggested Citation

  • Andrea Michiorri & Anna Maria Sempreviva & Sean Philipp & Paula Perez-Lopez & Alain Ferriere & David Moser, 2022. "Topic Taxonomy and Metadata to Support Renewable Energy Digitalisation," Energies, MDPI, vol. 15(24), pages 1-23, December.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9531-:d:1004856
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    References listed on IDEAS

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    1. Küçük, Dilek & Arslan, Yusuf, 2014. "Semi-automatic construction of a domain ontology for wind energy using Wikipedia articles," Renewable Energy, Elsevier, vol. 62(C), pages 484-489.
    2. Carlos Toledo & Alessandra Scognamiglio, 2021. "Agrivoltaic Systems Design and Assessment: A Critical Review, and a Descriptive Model towards a Sustainable Landscape Vision (Three-Dimensional Agrivoltaic Patterns)," Sustainability, MDPI, vol. 13(12), pages 1-38, June.
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    1. Shuo-Fang Liu & Yu-Shan Wei & Hong-Kai Guo & An-Yu Su, 2023. "An Application of Quality Function Deployment to Explore a Product Design Concept—A Case Study of a Triple-Effect Green Energy Generator for the Taiwan Environment," Sustainability, MDPI, vol. 15(24), pages 1-16, December.
    2. Rekha Guchhait & Biswajit Sarkar, 2023. "Increasing Growth of Renewable Energy: A State of Art," Energies, MDPI, vol. 16(6), pages 1-29, March.

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