Research on Harmonic Prediction and Regulation Strategy Based on Deep Learning

Photovoltaic power generation has been widely used because of its advantages of low energy consumption and low pollution with the development of China's dual-carbon policy. However, due to its randomness and access to a large number of power electronic equipment, photovoltaic grid-connected power generation leads to large randomness and volatility of electric energy and then produces harmonic problems. This paper studies the harmonic problems generated in the photovoltaic grid connection. First, the harmonic detection method is used to extract the required harmonics, and then the deep learning method is used to predict the next-moment harmonic. Finally, the harmonics in the power grid are eliminated by the active filter (APF). The current of the required base wave is finally obtained to complete the filtering of the current harmonics in the power grid.