彩神ll用户登录 With the continuous development of the new energy industry, my country's total wind power installed capacity and installed capacity have increased dramatically. How to improve the utilization rate of wind turbines, reduce the incidence and time of equipment failure, and avoid sudden equipment failures, has become the main goal of daily operation and maintenance of wind farms.

"Made in China 2025" released in May this year clearly stated that smart manufacturing is an important direction for the development of China's manufacturing industry. The intelligentization of wind turbines will be an important development trend of the wind power industry, and the intelligent development of wind turbines must be based on traditional manufacturing processes, fully integrate Internet technology innovation, and use new generation information technologies such as big data and cloud computing. Realize the background monitoring and full life cycle management of remote wind turbines to ensure optimal operation of wind turbines. As a result, digital smart wind farms have become a hot spot in the field of wind power development

Smart wind farms are mainly based on measurement and control technology, communication technology, information technology, big data processing technology and various intelligent algorithms to realize the automation of wind turbine control, the intelligence of equipment status perception and judgment, and the intelligence of operation and maintenance decision-making. Based on high-precision wind farm power prediction micro-site selection technology, big data medium-scale modeling technology and satellite remote sensing physical modeling technology to achieve smart micro-site selection, through more accurate big data and self-optimized wind farm power prediction, and Combine the power grid dispatching demand information and the status information of each wind turbine equipment to automatically adjust the output power of the wind turbine to meet the dispatching needs of the power grid; at the same time, it can intelligently diagnose the faults of each device, intelligently evaluate the equipment status, and combine operation and maintenance experience to achieve operation and maintenance Decision-making is automated and intelligent.