Intelligent Wireless Monitoring Technology for 10kV Overhead lines in Smart Grid Networks


  • Jiangang Lu Power dispatching control center of Guangdong Power Grid Co., Ltd., China
  • Shi Zhan Power dispatching control center of Guangdong Power Grid Co., Ltd., China
  • Xinzhan Liu Power dispatching control center of Guangdong Power Grid Co., Ltd., China



10kV overhead line, outage probability, simulation and analytic, analytical expression


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.


H. Wang and Z. Huang, “Guest editorial: WWWJ special issue of the 21th international conference on web information systems engineering (WISE 2020),” World Wide Web, vol. 25, no. 1, pp. 305–308, 2022.

B. Wang, F. Gao, S. Jin, H. Lin, and G. Y. Li, “Spatial- and frequency-wideband effects in millimeter-wave massive MIMO systems,” IEEE Trans. Signal Processing, vol. 66, no. 13, pp. 3393–3406, 2018.

R. Zhao and M. Tang, “Profit maximization in cache-aided intelligent computing networks,” Physical Commu-nication, vol. PP, no. 99, pp. 1–10, 2022.

H. Wang, J. Cao, and Y. Zhang, Access Control Management in Cloud Environments. Springer, 2020. [Online]. Available:

H. Wang, Y. Wang, T. Taleb, and X. Jiang, “Editorial: Special issue on security and privacy in network computing,” World Wide Web, vol. 23, no. 2, pp. 951–957, 2020.

L. Zhang and C. Gao, “Deep reinforcement learning based IRS-assisted mobile edge computing under physical-layer security,” Physical Communication, vol. PP, no. 99, pp. 1–10, 2022.

N. Dahlin and R. Jain, “Scheduling flexible nonpreemp-tive loads in smart-grid networks,” IEEE Trans. Control. Netw. Syst., vol. 9, no. 1, pp. 14–24, 2022.

E. Z. Serper and A. Altin-Kayhan, “Coverage and connectivity based lifetime maximization with topology update for WSN in smart grid applications,” Comput. Networks, vol. 209, p. 108940, 2022.

Z. Alavikia and M. Shabro, “A comprehensive layered approach for implementing internet of things-enabled smart grid: A survey,” Digit. Commun. Networks, vol. 8, no. 3, pp. 388–410, 2022.

S. Mishra, “Blockchain-based security in smart grid network,” Int. J. Commun. Networks Distributed Syst., vol. 28, no. 4, pp. 365–388, 2022.

X. Hu, J. Wang, and C. Zhong, “Statistical CSI based design for intelligent reflecting surface assisted MISO systems,” Science China: Information Science, vol. 63, no. 12, p. 222303, 2020.

J. Lu and M. Tang, “Performance analysis for IRS-assisted MEC networks with unit selection,” Physical Communication, p. 101869, 2022.

X. Hu, C. Zhong, Y. Zhu, X. Chen, and Z. Zhang, “Programmable metasurface-based multicast systems: Design and analysis,” IEEE J. Sel. Areas Commun., vol. 38, no. 8, pp. 1763–1776, 2020.

Y. Wu and C. Gao, “Task offloading for vehicular edge computing with imperfect CSI: A deep reinforcement approach,” Physical Communication, p. 101867, 2022.

X. Lai, J. Xia, L. Fan, T. Q. Duong, and A. Nallanathan, “Outdated access point selection for mobile edge com-puting with cochannel interference,” IEEE Transactions on Vehicular Technology, 2022.

R. Zhao and M. Tang, “Impact of direct links on intelligent reflect surface-aided MEC networks,” Physical Communication, vol. PP, no. 99, pp. 1–10, 2022.

D. Cai, P. Fan, Q. Zou, Y. Xu, Z. Ding, and Z. Liu, “Active device detection and performance analysis of massive non-orthogonal transmissions in cellular internet of things,” Science China information sciences, vol. 5, no. 8, pp. 182 301:1–182 301:18, 2022.

K. He and Y. Deng, “Efficient memory-bounded optimal detection for GSM-MIMO systems,” IEEE Trans. Commun., vol. 70, no. 7, pp. 4359–4372, 2022.

S. Tang and X. Lei, “Collaborative cache-aided relaying networks: Performance evaluation and system optimiza-tion,” IEEE Journal on Selected Areas in Communications, vol. PP, no. 99, pp. 1–12, 2022.

L. Chen and X. Lei, “Relay-assisted federated edge learn-ing:Performance analysis and system optimization,” IEEE Transactions on Communications, vol. PP, no. 99, pp. 1–12, 2022.

W. Zhou and X. Lei, “Priority-aware resource scheduling for uav-mounted mobile edge computing networks,” IEEE Trans. Vehic. Tech., vol. PP, no. 99, pp. 1–6, 2023.

S. Tang, “Dilated convolution based CSI feedback compression for massive MIMO systems,” IEEE Trans. Vehic. Tech., vol. 71, no. 5, pp. 211–216, 2022.

S. Tang and L. Chen, “Computational intelligence and deep learning for next-generation edge-enabled industrial IoT,” IEEE Trans. Netw. Sci. Eng., vol. 9, no. 3, pp. 105–117, 2022.

L. Chen, “Physical-layer security on mobile edge computing for emerging cyber physical systems,” Computer Communications, vol. 194, no. 1, pp. 180–188, 2022.




How to Cite

Lu J, Zhan S, Liu X. Intelligent Wireless Monitoring Technology for 10kV Overhead lines in Smart Grid Networks. EAI Endorsed Scal Inf Syst [Internet]. 2022 Nov. 8 [cited 2024 Jul. 15];10(2):e13. Available from: