Power Mutation Correction Technology for Photovoltaic Power Stations Based on the Internet of Things

With the continuous increase in the penetration of photovoltaic generation within power systems, the output power of PV stations is easily affected by factors such as solar irradiance, temperature, and environmental disturbances, leading to sudden power fluctuations that may cause grid instability and equipment malfunction. To address these challenges, this paper proposes a power mutation correction technology for photovoltaic power stations based on the Internet of Things. By establishing a multi-source perception-based power characteristic model and integrating a dynamic weighted correction equation with a distributed collaborative correction mechanism, the proposed method achieves rapid identification and real-time compensation of power mutations. Field validation conducted at a photovoltaic power station demonstrates that this method effectively improves correction accuracy, response speed, and system stability, providing technical support for intelligent operation and correction in photovoltaic power systems.