Research And Desing Of Remote Monitoring System For Distrbuted Photovoltaic Power Station Based On Cloud Platform

In 2021,China proposed to strive to achieve the "carbon peak" in 2030 and achieve the final goal of "carbon neutralization" in 2060.As a key link to achieve the double carbon goal,new energy resources also ushered in new development opportunities.As a new energy,photovoltaic power generation,with the support of national policy,the cumulative grid-connected photovoltaic installed capacity in China reaches 305.98 GW by the end of 2021,of which the proportion of distributed photovoltaic power stations increased from 14% in 2015 to 35.1%.Because distributed photovoltaic power stations are scattered,data transmission,monitoring and unified management are difficult.With the increase of application scale and the expansion of application area,its remote centralized monitoring is of great significance to optimize photovoltaic power stations and increase the generation revenue.In view of the present distributed photovoltaic power station is more dispersed,informationization level is low,late is bad for monitoring,management and maintenance problems of photovoltaic power station monitoring system in this paper,the present research situation and the use of sensor technology,wireless communication technology,the Internet of things technology,cloud platform technology,design the distributed photovoltaic power station remote monitoring system based on cloud platform.The system uses Lo Ra for on-site wireless data collection and NB-iot terminals for off-site data interaction to expand wireless coverage and reduce the number of terminals interacting with external data.Using cloud server for development,through calling One NET cloud platform API interface to achieve data call and push;Open source Tomcat server,My SQL database,SSM framework and Bootstrap framework are used for front-end and back-end development,and the functions of login registration,real-time monitoring,historical data query,personnel management and fault alarm of the monitoring system are finally realized.In terms of short-term pv output prediction,PCA was used to reduce the dimensionality of the original feature data,and GWO algorithm was used to optimize the Elamn neural network,so as to build the PCAGWA-Elman pv short-term output prediction model.MATLAB simulation shows that the prediction effect of the model is good.This paper tests the Lo Ra wireless transmission module communication,gateway maximum load,NB-Io T wireless transmission module of a distributed photovoltaic power station in South China.The results show that the system is stable and reliable,high data acquisition accuracy,and normal Web functions,and can meet the remote monitoring requirements of distributed photovoltaic power stations.In addition,the designed remote monitoring system for distributed photovoltaic power stations based on cloud platform has the characteristics of simple operation,fast response,strong scalability,and has good market application prospects.