Big Data Energy Systems: A Survey of Practices and Associated Challenges
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912501070823424 |
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| author | Mwinuka, Lunodzo J. Cafaro, Massimo Pereira, Lucas Morais, Hugo |
| author_facet | Mwinuka, Lunodzo J. Cafaro, Massimo Pereira, Lucas Morais, Hugo |
| contents | Energy systems generate vast amounts of data in extremely short time intervals, creating challenges for efficient data management. Traditional data management methods often struggle with scalability and accessibility, limiting their usefulness. More advanced solutions, such as NoSQL databases and cloud-based platforms, have been adopted to address these issues. Still, even these advanced solutions can encounter bottlenecks, which can impact the efficiency of data storage, retrieval, and analysis. This review paper explores the research trends in big data management for energy systems, highlighting the practices, opportunities and challenges. Also, the data regulatory demands are highlighted using chosen reference architectures. The review, in particular, explores the limitations of current storage and data integration solutions and examines how new technologies are applied to the energy sector. Novel insights into emerging technologies, including data spaces, various data management architectures, peer-to-peer data management, and blockchains, are provided, along with practical recommendations for achieving enhanced data sharing and regulatory compliance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_19154 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Big Data Energy Systems: A Survey of Practices and Associated Challenges Mwinuka, Lunodzo J. Cafaro, Massimo Pereira, Lucas Morais, Hugo Databases Distributed, Parallel, and Cluster Computing Energy systems generate vast amounts of data in extremely short time intervals, creating challenges for efficient data management. Traditional data management methods often struggle with scalability and accessibility, limiting their usefulness. More advanced solutions, such as NoSQL databases and cloud-based platforms, have been adopted to address these issues. Still, even these advanced solutions can encounter bottlenecks, which can impact the efficiency of data storage, retrieval, and analysis. This review paper explores the research trends in big data management for energy systems, highlighting the practices, opportunities and challenges. Also, the data regulatory demands are highlighted using chosen reference architectures. The review, in particular, explores the limitations of current storage and data integration solutions and examines how new technologies are applied to the energy sector. Novel insights into emerging technologies, including data spaces, various data management architectures, peer-to-peer data management, and blockchains, are provided, along with practical recommendations for achieving enhanced data sharing and regulatory compliance. |
| title | Big Data Energy Systems: A Survey of Practices and Associated Challenges |
| topic | Databases Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2507.19154 |