Research On Intelligent Monitoring System Of High Voltage Switchgear Based On LPWAN

As the most important power equipment in the power system,the high-voltage switchgear plays the role of on-off,control and protection of power lines in the fields of power generation,transmission,and distribution.During the long-term operation of the switch cabinet,it is susceptible to problems such as aging insulation performance,misoperation,and overheating of the contacts in the cabinet,which cause electrical faults,which affect the safety and stability of the power system.Therefore,this paper combines a high-voltage equipment state awareness technology,low-power wide area network(LPWAIN)technology,cloud computing,edge computing technology,and artificial intelligence algorithms to propose a multi-source information fusion high-voltage switch cabinet monitoring method to achieve Real-time monitoring and fault diagnosis of the operation status of all switch cabinets.Firstly,this paper designs a monitoring scheme for the parameters in the cabinet by analyzing the internal structure of the high-voltage switchgear and its prone nodes and causes of failure.Aiming at the problems of uneven distribution of high-voltage switchgear equipment in power lines,data transmission caused by many monitoring parameters in the cabinet,and scattered monitoring nodes.This paper combines the technical advantages of LoRa and NB-IoT,and designs the LPWAN network structure of LoRa ad hoc network awareness and NB-IoT convergence upload.Secondly,for the large amount of data generated by the high-voltage switchgear during the work process,it caused problems such as greater pressure on system communication and server data processing.In this paper,the edge cloud collaborative data processing mechanism is used to improve the data processing and storage methods of the traditional high-voltage switchgear monitoring system,and the edge intelligent processing model based on the adaptive threshold algorithm is optimized.After verification,this method significantly reduces the problem of monitoring node data redundancy and improves system data's transmission efficiency.By establishing a PCA-PNN multi-source information fusion fault diagnosis model for power equipment,the system solves the problem of multi-sourced monitoring data of the perception layer,and performs diagnostic analysis and fault early warning on the operating status of the high-voltage switchgear.Finally,the paper tests the system's key technologies and system performance separately,and analyzes the test results.The results show that the performance of the intelligent monitoring system of the high voltage switchgear designed in this paper meets the design requirements.It can improve the data transmission efficiency and real-time performance of the switchgear monitoring system,and realize the functions of online monitoring and fault diagnosis and early warning of the switchgear,which has high research significance.Fig.[47]table[11]reference[84]...