A novel real-time monitoring system for photovoltaic(PV)generation is presented in this paper.Internet of Things(IoT)integrated with cloud servers and terminal applications allow the remote monitoring of centralized o...A novel real-time monitoring system for photovoltaic(PV)generation is presented in this paper.Internet of Things(IoT)integrated with cloud servers and terminal applications allow the remote monitoring of centralized or distributed pho-tovoltaic systems.The proposed system could realize the net-working communication of multiple nodes based on ZigBee,and upload the operational data to the cloud server via a 4G communications network.Then,the server selects three-phase current as the sample sets from the uploaded data to set up a composite current characteristic combining wavelet packet en-ergy with waveform parameter,and establishes a fault diagnosis model based on the probabilistic neural network to analyze the health status of the PV inverter online.This method requires little sampling frequency without an extra signal and saves the cost of local devices by placing online diagnostics on the server-side.In addition,the user could query and store the running information of the PV systems through the personal computer-side web or mobile phone with remote control.This article presents the hardware design of ZigBee and the 4G module,and composition of the diagnosis model for open circuit failure of the PV inverter through the cloud server,building the user software at the application layer.The final experimental results show that the proposed system has better communication performance and higher diagnostic accuracy in real-time monitoring.展开更多
基金This work was supported in part by the National Natural Science Foundation of China under grant no.51207091the Key Project of National Natural Science Foundation of China under grant no.51637001/E070701.
文摘A novel real-time monitoring system for photovoltaic(PV)generation is presented in this paper.Internet of Things(IoT)integrated with cloud servers and terminal applications allow the remote monitoring of centralized or distributed pho-tovoltaic systems.The proposed system could realize the net-working communication of multiple nodes based on ZigBee,and upload the operational data to the cloud server via a 4G communications network.Then,the server selects three-phase current as the sample sets from the uploaded data to set up a composite current characteristic combining wavelet packet en-ergy with waveform parameter,and establishes a fault diagnosis model based on the probabilistic neural network to analyze the health status of the PV inverter online.This method requires little sampling frequency without an extra signal and saves the cost of local devices by placing online diagnostics on the server-side.In addition,the user could query and store the running information of the PV systems through the personal computer-side web or mobile phone with remote control.This article presents the hardware design of ZigBee and the 4G module,and composition of the diagnosis model for open circuit failure of the PV inverter through the cloud server,building the user software at the application layer.The final experimental results show that the proposed system has better communication performance and higher diagnostic accuracy in real-time monitoring.
