智能电网中10kV架空线智能无线监控技术

IF 1.1 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS EAI Endorsed Transactions on Scalable Information Systems Pub Date : 2022-11-08 DOI:10.4108/eetsis.v10i1.2527
Jiangang Lu, Zhan Shi, Xinzhan Liu
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引用次数: 4

摘要

在信息技术快速发展的推动下,10kV架空线路已在大多数城市得到广泛应用,对配电网进行有效监控,以保证系统的正常运行具有重要意义。传统的配电网监测方法大多以人工为主,给配电网故障定位、抢修、维护和实时监控带来不便,降低了配电网应急抢修的效率和供电的可靠性。针对10kV架空网络的自动监控问题,本文采用智能无线监控技术,通过无线链路,利用监控节点对网络传输状态进行监控。我们根据无线信道上的无线数据速率,使用中断概率度量来评估系统监控性能。对于所考虑的系统,我们导出了分析中断概率,以便在信噪比(SNR)的整个范围内测量系统的性能。最后给出了仿真结果,验证了本文关于系统监控中断概率的解析表达式。
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Intelligent Wireless Monitoring Technology for 10kV Overhead lines in Smart Grid Networks
Promoted by the rapid development of information technology, 10kV overhead line has been widely used in the majority of cities, and it is of great significance to monitor the distribution network effectively, in order to ensure the normal operation of the system. Most of traditional distribution network monitoring methods are based on manual work, which causes inconvenience to the distribution network fault location, repair, maintenance and real-time monitoring, and reduces the efficiency of the distribution network emergency repair and the reliability of power supply. Aiming at the automatic monitoring problem of 10kV overhead network, this paper adopts an intelligent wireless monitoring technology, where a monitoring node is employed to monitor the network transmission status through wireless links. We evaluate the system monitoring performance by using the metric of outage probability, depending on the wireless data rate over wireless channels. For the considered system, we derive analytical outage probability, in order to measure the system performance in the whole range of signal-to-noise ratio (SNR). The simulation results are finally presented to verify the analytical expressions on the system monitoring outage probability in this paper.
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来源期刊
EAI Endorsed Transactions on Scalable Information Systems
EAI Endorsed Transactions on Scalable Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
2.80
自引率
15.40%
发文量
49
审稿时长
10 weeks
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