Research on big data batch and stream analysis technology of 5G charging station based on Flink

Yan Chen; Yang Ma; Jian Fang; Xiaoning Jiang

doi:10.1117/12.2618244

29 November 2021 Research on big data batch and stream analysis technology of 5G charging station based on Flink

Yan Chen, Yang Ma, Jian Fang, Xiaoning Jiang

Proceedings Volume 12080, 4th International Symposium on Power Electronics and Control Engineering (ISPECE 2021); 120800I (2021) https://doi.org/10.1117/12.2618244
Event: 4th International Symposium on Power Electronics and Control Engineering (ISPECE 2021), 2021, Nanchang, China

Abstract

With the rapid growth of the number of electric vehicles in society, their random charging will have an impact on the power grid. In the 5g era, the real-time and reliability of charging station data acquisition and transmission are significantly improved, and the analysis and application of charging data become particularly critical. This paper first puts forward the 3c3c model of 5g charging station, and then studies the corresponding big data batch and stream analysis technology by combining this model with Flink framework, so as to better serve the business of 5g charging station in the future.

Citation Download Citation

Yan Chen, Yang Ma, Jian Fang, and Xiaoning Jiang "Research on big data batch and stream analysis technology of 5G charging station based on Flink", Proc. SPIE 12080, 4th International Symposium on Power Electronics and Control Engineering (ISPECE 2021), 120800I (29 November 2021); https://doi.org/10.1117/12.2618244

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