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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1018))

Abstract

The coal-fired power plant regularly produces enormous amounts of data from its sensors, control and monitoring systems. The Volume of this data will be increasing due to widely available smart meters, Wi-Fi devices and rapidly developing IT systems. Big data technology gives the opportunity to use such types and volumes of data and could be an adequate solution in the areas, which have been untouched by information technology yet. This paper describes the possibility to use big data technology to improve internal processes on the example of a coal-fired power plant. Review of applying new technologies is made from an internal point of view, drawing from the professional experience of the authors. We are taking a closer look into the power generation process and trying to find areas to develop insights, hopefully enabling us to create more value for the industry.

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Acknowledgements

This work was supported by the Polish Ministry of Science and Higher Education as part of the Implementation Doctorate program at the Silesian University of Technology, Gliwice, Poland (contract No 0053/DW/2018), and partially, by the pro-quality grant for highly scored publications or issued patents of the Rector of the Silesian University of Technology, Gliwice, Poland (grant No 02/020/RGJ19/0167), and by Statutory Research funds of Institute of Informatics, Silesian University of Technology, Gliwice, Poland (grant No BK/204/ RAU2/2019).

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Correspondence to Marek Moleda or Dariusz Mrozek .

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Moleda, M., Mrozek, D. (2019). Big Data in Power Generation. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Paving the Road to Smart Data Processing and Analysis. BDAS 2019. Communications in Computer and Information Science, vol 1018. Springer, Cham. https://doi.org/10.1007/978-3-030-19093-4_2

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  • DOI: https://doi.org/10.1007/978-3-030-19093-4_2

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  • Online ISBN: 978-3-030-19093-4

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