Author:
Lu Xin,Gu Yu,Liu Changqing,Ye Qiangbin,Chen Kuiyin
Abstract
Abstract
The remote terminal equipment data collection system of distribution automation plays a decisive role in the monitoring of distribution networks. The thesis studies the key technologies of distribution network operation and real-time data collection of topology data, analyses various new technologies of ICT, designs the basic technical architecture of real-time data collection, and realizes the automatic connection of various professional data of distribution networks such as equipment, marketing, and scheduling. Into a unified distribution network database that integrates various disciplines, multiple themes, and multiple applications, comprehensively improves the quality of distribution network data, and provides a basis for distribution network diagnosis and big data analysis. At the same time, the paper performs software filtering on the data and uses fast Fourier transform to improve real-time performance. Using a signal generator and a high-precision switching power supply as the signal input, the frequency test, voltage accuracy test and fast Fourier transform experiment were conducted respectively. The experimental results show that the simplified terminal data collection system has higher accuracy and stability.
Reference6 articles.
1. Forecasting of passenger flow's distribution among urban rail transit stations based on afc data;Cai;Zhongguo Tiedao Kexue/China Railway ence,2015
2. Estimation method of passenger route choice proportion in urban rail transit based on afc data;Shi;Dongnan Daxue Xuebao,2015
3. Calibration and data collection protocols for reliable lattice parameter values in electron pair distribution function studies;Abeykoon;Journal of Applied Crystallography,2015
4. Automation and experience of controlled crystal dehydration: results from the european synchrotron hc1 collaboration;Bowler;Crystal Growth & Design,2015
5. Cooperative sensing data collection and distribution with packet collision avoidance in mobile long-thin networks;Chen;Sensors,2018
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