Power Prediction and Regulation of Photovoltaic Power Generation System Based on Kalman Filter

In view of the limitations of the traditional Fibonacci sequence algorithm in the power prediction and regulation of photovoltaic power generation system, a power prediction and adjustment scheme based on Kalman filter is proposed. Firstly, the influencing factors is accurately located through the linear system state theory, and the indicators is reasonably divided to reduce interference, and the power prediction and adjustment scheme is constructed by using Kalman filter. Experimental results show that under certain evaluation criteria, the proposed scheme is superior to the traditional Fibonacci algorithm in terms of power prediction and adjustment accuracy, and processing time of influencing factors, and has obvious advantages. Power prediction and regulation plays an extremely important role in photovoltaic power generation systems, which can accurately predict and optimize the growth characteristics and product generation of photovoltaic power generation systems. However, the traditional Fibonacci algorithm has some limitations in solving the power simulation problem of power generation system, especially when dealing with complex problems. In this paper, a power prediction and regulation scheme based on Kalman filter is proposed to better solve this problem. In this scheme, the influencing factors is accurately located through the linear system state theory, so as to determine the division of indicators, and the scheme is constructed by using Kalman filter. Experimental results show that under certain evaluation criteria, the accuracy and speed of the scheme is significantly improved for different problems, and it has better performance. Therefore, the simulation scheme based on Kalman filter in the power prediction and regulation of photovoltaic power generation system can better solve the limitations of the traditional Fibonacci sequence algorithm and improve the simulation accuracy and efficiency.