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.
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Wang, J., Xu, Y., Jiang, C., Yan, J., Ding, B., Lin, Q. (2024). Application of Big Data Processing Technology in Power Consumption Information Acquisition. In: Wang, B., Hu, Z., Jiang, X., Zhang, YD. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 534. Springer, Cham. https://doi.org/10.1007/978-3-031-50577-5_28
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DOI: https://doi.org/10.1007/978-3-031-50577-5_28
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