Integrated intelligent management and control system for million-kilowatt photovoltaic stations

This study addresses the management challenges of million-kilowatt photovoltaic (PV) stations by proposing an integrated intelligent management and control system.The system combines IoT sensing, edge computing, and AI to achieve dynamic collaborative management.Deployed in a 1 GW demonstration station, the system integrates 256 edge computing nodes covering 128,000 PV arrays.Results show that the average conversion efficiency increased by 2.3%, fault recognition accuracy reached 98.6%, and equipment abnormality response time shortened to 30 seconds.Additionally, combining weather forecasts with grid load data increased annual power generation by 5.8%.Security testing confirms that core function availability exceeds 98% under extreme conditions.The research validates that this cloud-edge collaborative architecture significantly enhances the reliability, economy, and operational efficiency of large-scale PV plants, offering a replicable path for the industry.