AI helps intelligent operation and maintenance of photovoltaic power plants.
Addtime：2023-02-08 ClickS：1552
AI helps intelligent operation and maintenance of photovoltaic power plants.
With the reduction of photovoltaic subsidies year by year, it is increasingly important to improve the revenue of photovoltaic power plants through operation and maintenance. The inefficiency and high cost of traditional operation and maintenance can no longer meet the needs of operation and maintenance. With the rapid development of artificial intelligence and big data analysis technology, the operation and maintenance of photovoltaic power plants has also entered the intelligent stage with online to offline.
Based on this, Mulianneng has developed an intelligent operation and maintenance platform for photovoltaic power stations based on AI technology and big data technology, which is user-centered. By improving the operation and maintenance level of power stations, the revenue of power stations can finally be improved. In order to meet the different needs of various customers for operation and maintenance, based on the original professional version, Mulian Neng has specially launched a standard version and a simple version system with higher cost performance, practicality and ease of use, which can not only meet the intelligent operation and maintenance management of a single power station, but also meet the intelligent centralized operation and maintenance management of multiple power stations.
AI technology
1) Intelligent data acquisition
The system uses machine vision to clean the collected data, so as to verify and supplement the correctness of the collected data. According to the set cleaning conditions, the system removes and filters the abnormal data and supplements the missing data, thus ensuring the accuracy and integrity of the collected data and providing the basic guarantee for the later data analysis.
2) Intelligent fault alarm
Based on a large number of fault information of photovoltaic power stations and their causes, the system conducts model training and establishes a model base of common alarm information and causes of new energy power stations. By using intelligent search and reasoning technology, the real-time operation data and historical data of each power station are comprehensively analyzed, and the hidden faults of each power station are obtained in time and alarm prompts are given. It mainly includes data exceeding the limit, equipment alarm, remote signal displacement, equipment failure, insufficient inventory, sub-health equipment, and liftable nodes. So that users can know the abnormal information existing in the power station at the first time.
3) Automatically create and assign defects.
The system combines the real-time collected data and the analysis results of historical data, and uses autonomous learning technology to perceive the fault information of the power station, and automatically creates a defect list according to the fault content. At the same time, the system locates the real-time position of each operation and maintenance personnel according to the mobile individual equipment, and intelligently distributes the defect list to the personnel closest to the fault point, thus maximizing the operation and maintenance efficiency and reducing the fault intensity. Users know the abnormal information in the power station at the first time.
4) Intelligent inspection
The system is seamlessly connected with the mobile individual soldiers, realizing visual and intelligent patrol operation, effectively carrying out remote patrol command, patrol trajectory monitoring, patrol process playback, patrol task distribution, patrol result feedback and other work, grasping the progress and results of patrol work in real time, enhancing the stability, reliability and controllability of patrol work, ensuring the quality of patrol work, effectively reducing the accident rate and improving the work efficiency of personnel.
5) Intelligent trend analysis
The system combines a large number of historical radiation data and electricity data of photovoltaic power stations, and establishes an accurate and reliable prediction model through data mining and reasoning technology. So as to predict the power generation, income and other information of the power station in the 25-year life cycle. Provide data basis for the planned power generation of the power station.
With the reduction of photovoltaic subsidies year by year, it is increasingly important to improve the revenue of photovoltaic power plants through operation and maintenance. The inefficiency and high cost of traditional operation and maintenance can no longer meet the needs of operation and maintenance. With the rapid development of artificial intelligence and big data analysis technology, the operation and maintenance of photovoltaic power plants has also entered the intelligent stage with online to offline.
Based on this, Mulianneng has developed an intelligent operation and maintenance platform for photovoltaic power stations based on AI technology and big data technology, which is user-centered. By improving the operation and maintenance level of power stations, the revenue of power stations can finally be improved. In order to meet the different needs of various customers for operation and maintenance, based on the original professional version, Mulian Neng has specially launched a standard version and a simple version system with higher cost performance, practicality and ease of use, which can not only meet the intelligent operation and maintenance management of a single power station, but also meet the intelligent centralized operation and maintenance management of multiple power stations.
AI technology
1) Intelligent data acquisition
The system uses machine vision to clean the collected data, so as to verify and supplement the correctness of the collected data. According to the set cleaning conditions, the system removes and filters the abnormal data and supplements the missing data, thus ensuring the accuracy and integrity of the collected data and providing the basic guarantee for the later data analysis.
2) Intelligent fault alarm
Based on a large number of fault information of photovoltaic power stations and their causes, the system conducts model training and establishes a model base of common alarm information and causes of new energy power stations. By using intelligent search and reasoning technology, the real-time operation data and historical data of each power station are comprehensively analyzed, and the hidden faults of each power station are obtained in time and alarm prompts are given. It mainly includes data exceeding the limit, equipment alarm, remote signal displacement, equipment failure, insufficient inventory, sub-health equipment, and liftable nodes. So that users can know the abnormal information existing in the power station at the first time.
3) Automatically create and assign defects.
The system combines the real-time collected data and the analysis results of historical data, and uses autonomous learning technology to perceive the fault information of the power station, and automatically creates a defect list according to the fault content. At the same time, the system locates the real-time position of each operation and maintenance personnel according to the mobile individual equipment, and intelligently distributes the defect list to the personnel closest to the fault point, thus maximizing the operation and maintenance efficiency and reducing the fault intensity. Users know the abnormal information in the power station at the first time.
4) Intelligent inspection
The system is seamlessly connected with the mobile individual soldiers, realizing visual and intelligent patrol operation, effectively carrying out remote patrol command, patrol trajectory monitoring, patrol process playback, patrol task distribution, patrol result feedback and other work, grasping the progress and results of patrol work in real time, enhancing the stability, reliability and controllability of patrol work, ensuring the quality of patrol work, effectively reducing the accident rate and improving the work efficiency of personnel.
5) Intelligent trend analysis
The system combines a large number of historical radiation data and electricity data of photovoltaic power stations, and establishes an accurate and reliable prediction model through data mining and reasoning technology. So as to predict the power generation, income and other information of the power station in the 25-year life cycle. Provide data basis for the planned power generation of the power station.
