Development Of Intelligent Monitoring And Operation System For Photovoltaic Station

In recent years,the photovoltaic industry has developed rapidly,and the number and capacity of power stations are increasing.However,power stations are widely distributed and have a large number of equipment,which face problems related to remote centralized monitoring,real-time monitoring,centralized operation and maintenance management.At present,the research on centralized monitoring and operation and maintenance management at home and abroad mainly focuses on the level of power station,and there are still problems such as not comprehensive enough,insufficient data analysis ability,and insufficient intelligence degree.In view of the above problems,according to the general idea of "centralized monitoring--regional maintenance--site security",this paper developed a set of intelligent real-time monitoring and operation system of photovoltaic power station to realize the unification of remote centralized control,real-time monitoring and production operation management of photovoltaic power station.In particular,the research focuses on intelligent fault diagnosis and operation and maintenance of photovoltaic power station.The specific work of the paper is as follows:1.Study the status quo of intelligent monitoring and operation and maintenance system of photovoltaic power station at home and abroad.Based on the limitations of the current status quo,clarify the system development ideas,and focus the core of system design on the design of fault classification model and the research of UAV autonomous navigation and inspection strategy,so as to help solve the actual operation and maintenance problems of photovoltaic power station.2.By analyzing the main fault types of photovoltaic power station,this paper studies a fault classification model of photovoltaic power station based on support vector machine.In order to solve the problem of insufficient training data for fault classification of photovoltaic power station,an accelerated simulation system of photovoltaic power station is designed.Through this classification model,the aging,cloud cover and fixed cover faults of PV modules can be effectively classified;Through the accelerated simulation system of photovoltaic power station,the acquisition of fault data close to the real scene is realized,which provides a basis for the training of the overall classification model.Experiments show that the classification model has good performance and classification accuracy.3.By analyzing the main fault types of photovoltaic power station,this paper studies a fault classification model of photovoltaic power station based on support vector machine.In order to solve the problem of insufficient training data for fault classification of photovoltaic power station,an accelerated simulation system of photovoltaic power station is designed.Through this classification model,the aging,cloud cover and fixed cover faults of PV modules can be effectively classified;Through the accelerated simulation system of photovoltaic power station,the acquisition of fault data close to the real scene is realized,which provides a basis for the training of the overall classification model.The experimental results show that the classification model has good performance and classification accuracy.Firstly,in order to ensure that the UAV can effectively track the centerline of PV string,a flight speed control and flight direction steering scheme based on the centerline position information of PV string is proposed;Then,a PV string recognition and location algorithm combining color,gradient and shape features is proposed to determine the PV string position.Finally,the effectiveness and feasibility of the scheme are proved in practical application.4.Based on the key technologies of fault diagnosis and operation and maintenance inspection,this paper develops a set of intelligent monitoring and operation and maintenance system for photovoltaic power station in combination with the actual situation of a company’s photovoltaic power station,makes an overall evaluation of the system application and benefits,and looks forward to the direction of research and improvement in the next stage.