Second-Level Photovoltaic Power Forecasting Based on Improved Pix2PixHD Image Restoration

The fundamental cause of severe output fluctuations in photovoltaic (PV) power plants is the abrupt change in ground irradiance due to cloud cover. To enhance the accuracy of PV power forecasting under cloud cover conditions, this article proposes a second level power forecasting method for PV power plants based on an improved Pix2PixHD image restoration algorithm. First, the PV plant model is constructed based on the actual layout by applying Newton Raphson method. Second, the data characteristics of PV power output from the inverters are deeply explored to analyze the mapping relationship between PV power and irradiance. A virtual cloud image is constructed to represent the cloud cover (power loss) situation by describing the shape, thickness, and movement direction of the clouds. Subsequently, the virtual cloud images were preprocessed using the Canny edge detector, followed by restoration of the processed defective virtual cloud images using the Improved Pix2PixHD image restoration algorithm. Finally, a high-precision PV power forecasting at second level is achieved based on the linear relationship between PV power, irradiance, and pixel values of the virtual cloud image.