Big Data Аnalysis in Smart Grid Systems

Yu Jun, Olena Hordiichuk-Bublivska, Yan Lingyu, Marian Kyryk, Mykola Beshley, Hu Jiwei

Abstract

The problem of Big Data processing in large industrial systems requires the use of machine learning methods. A smart grid system is an example of improving the efficiency of traditional data processing systems, which allows much more efficient and flexible distribution of electricity to end-users. However, for a smart grid to work properly, it needs to constantly monitor data from sensors and meters. The Singular Value Decomposition (SVD) algorithm is used to improve the efficiency of Big Data processing and reduce its dimensionality. The paper proposes the use of advanced SVD, which can work in distributed industrial systems and ensure the reliability and speed of data processing.

Keywords

Smart grid; Industrial Internet of Things; Federated Machine Learning; Affordable and Clean Energy; Big Data; Singular Value Decomposition

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IMEKO-TC10-2022-019.pdf

DOI

10.21014/tc10-2022.019

IMEKO TC

TC10 - Measurement for Diagnostics, Optimization and Control

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