Research Article
Application of Big Data Processing Technology in Power Consumption Information Acquisition
@INPROCEEDINGS{10.1007/978-3-031-50577-5_28, author={Jin Wang and Yukun Xu and Chao Jiang and Jingrui Yan and Bo Ding and Qiusheng Lin}, title={Application of Big Data Processing Technology in Power Consumption Information Acquisition}, proceedings={Multimedia Technology and Enhanced Learning. 5th EAI International Conference, ICMTEL 2023, Leicester, UK, April 28-29, 2023, Proceedings, Part III}, proceedings_a={ICMTEL PART 3}, year={2024}, month={2}, keywords={Big Data Processing Technology Power Consumption Information Information Collection}, doi={10.1007/978-3-031-50577-5_28} }- Jin Wang
Yukun Xu
Chao Jiang
Jingrui Yan
Bo Ding
Qiusheng Lin
Year: 2024
Application of Big Data Processing Technology in Power Consumption Information Acquisition
ICMTEL PART 3
Springer
DOI: 10.1007/978-3-031-50577-5_28
Abstract
In the big data environment of power enterprise operation, power consumption information plays an important role in user behavior monitoring and power generation task planning. In order to provide effective information reference for power work, big data processing technology is applied to optimize the design of power information acquisition method. According to the composition structure and working principle of the power network, the power network model is constructed. The power information collector and processor are installed, and the A/D conversion circuit is used to complete the A/D conversion of the power information acquisition signal. Synchronously control the power consumption information acquisition program, and use big data processing technology to count the power consumption information parameters, such as electricity consumption and electricity charges. Through noise filtering, missing value compensation and other steps, the pretreatment of the information collected at sea is completed, so as to realize the collection of electricity information. Compared with the traditional acquisition method, it is found that the acquisition error of the optimal design method in the two aspects of electricity consumption and electricity cost is reduced by 0.345 kWh, 0.095 yuan, reducing the redundancy of the acquisition information, and improving the integrity of the acquisition information.
