Research And Development Of Monitoring System For Solar Charging Station

In order to alleviate the energy crisis and the charging pressure of new energy electric vehicles,and combined with the characteristics of wide distribution and easy access to solar energy,solar charging stations have become a research hotspot.However,the existing densely large-scale solar charging stations need to be manned,which has problems such as high operating costs,low charging efficiency,and high power consumption.In response to the above problems,the thesis introduces energy-saving prediction algorithms in the solar charging station monitoring system to realize the monitoring data prediction function,reduce power consumption,and design and develop the monitoring system of the charging station.First of all,the thesis summarizes the research background,significance and status quo of the subject,and clarifies the research objectives and c ontent of the thesis.According to the needs of solar charging stations,the overall framework of its monitoring system is designed.On this basis,the thesis uses "ZigBee+4G" communication means to construct a wireless sensor network composed of data acquisition nodes and gateway nodes,and selects and designs each functional module of the node one by one.Secondly,determine the hardware modules of the solar charging station monitoring system,including MCU module,CPU module,ZigBee module,4G module and power supply module,which are used to realize the timing collection and upload of data and the issuing control of instructions.Then,in order to realize the energy saving of each device in the charging station,the system selects the CC2530 chip,through the modification and design of the MAC layer of the protocol stack,the thesis realizes the re-networking of terminal nodes,routing nodes and coordinator nodes,and introduces an adaptive energy-saving sleep algorithm to reduce energy consumption.Finally,for the application scenarios of large-scale node deployment,the thesis combines the adaptive three-time exponential smoothing algorithm on the basis of adaptive sampling scheduling,which improves the sampling accuracy while reducing energy consumpti on.In terms of software,the thesis designes a remote monitoring system consisting of a wireless sensor network,a cloud platform and a web server.Alibaba Cloud was selected to build the cloud data center and cloud service center of the system,and the host computer and web application platform of the monitoring system were designed with Visual Studio 2019 software.The software constitutes a human-computer interaction platform with elements such as forms,pictures,and curves.Users can view the monitoring information of the charging station through the Web platform at any time.Finally,this thesis complete the test of the entire monitoring system.Tests have proved that the charging system designed in this thesis,which integrates data collection,transmission,processing,and monitoring,and can be applied to various large and dense solar charging station systems with high feasibility and stable operation,and can be realized the expected goal of system information monitoring and data analysis.