Development Of Fault Monitoring System For Photovoltaic Module In Solar Power Station

With the aggravation of energy crisis and environmental crisis,solar energy as a renewable and clean energy has attracted worldwide attention.In this trend,the development of photovoltaic power generation is very rapid.At the same time,with the increasing scale of photovoltaic power plants,it is more and more urgent to monitor them effectively so as to grasp the working conditions of the power plants.As the core of the power plant,photovoltaic module has a huge number,and often works in harsh environment.It is prone to failure due to the erosion of wind,sand and rain,which affects the power generation efficiency of the power plant.However,the existing monitoring system for photovoltaic power plants mainly focuses on the junction box,DC cabinet and inverters,which can not effectively monitor the bottom photovoltaic modules,and can not effectively diagnose the failure of the modules.Therefore,aiming at the above problems of the monitoring system of photovoltaic power station,a wireless fault monitoring system for photovoltaic modules of solar power station is developed,which combines the ZigBee wireless sensor network with low cost and strong flexibility.This paper mainly includes two aspects: the research of photovoltaic module fault diagnosis method and the development of software and hardware of fault monitoring system.Aiming at the fault diagnosis method,a fault diagnosis method based on photovoltaic module mathematical model and SRF classification model is proposed in this paper.That is to say,whether the deviation between the theoretical voltage and the actual output voltage exceeds the threshold value is used to judge whether the component is abnormal or not.If the photovoltaic module is abnormal,the number of abnormalities will be increased by one.When the number of abnormalities exceeds the threshold,the module will be judged as a suspected fault,and then the SRF classification model will be used to judge its specific working state.For this purpose,the following work has been done in this paper:(1)To improve the shortcomings of the traditional PSO algorithm,a GCPSO algorithm is obtained to extract the internal parameters of PV by introducing the Gauss weighting method;(2)Revise the empirical formula of internal parameters and establish a more accurate mathematical model of photovoltaic modules under any operating conditions;(3)The output characteristic curves of photovoltaic modules under different states are analyzed,and the rules are summarized,and the characteristic parameters that can reflect the state characteristics are selected;(4)To improve the unreasonable voting mechanism of RF algorithm by using Stacking method,a SRF algorithm is proposed,and the above characteristic parameters are used as the attributes of the algorithm to train the SRF classification model for judging the status of photovoltaic modules.Aiming at the development of software and hardware of fault monitoring system,the following work has been done in this paper:(1)Analyzing the workflow of Zstack-2.5.1a protocol stack,setting up custom event handling function,and selecting mesh as the topology of ZigBee network;(2)The ZigBee node of the fault monitoring system is developed with CC2530 as the core control chip,including the development of voltage and current acquisition circuit,power supply circuit and curve scanning circuit.(3)Based on Zstack-2.5.1a protocol stack,the ZigBee node of the fault monitoring system is programmed so that it can respond to the instructions of the upper computer to collect data and scan the characteristic curve.(4)Upper computer software is developed based on LabVIEW development platform and Access database technology.The monitoring data are analyzed,stored and displayed on it.The mathematical model of photovoltaic module and SRF classification model are embedded into software through MATLAB script to develop fault diagnosis function.Through the experimental test,the fault monitoring system runs stably.it can effectively monitor the photovoltaic module and reflect various types of photovoltaic module failures,and the functions of the system generally meet the expected design requirements.