Second-level Photovoltaic Power Forecasting Method Based on pix2pixHD Image Restoration
The fundamental reason for the drastic fluctuations in the output of photovoltaic power plants is the obstruction of cloud clusters leading to transient changes in ground irradiance.In order to improve the accuracy of photovoltaic power forecasting under cloud cover,this paper proposes a photovoltaic power forecasting method at the second level based on pix2pixHD image restoration.Firstly,a refined model of the photovoltaic power plant is derived based on the parameters of photovoltaic components,the arrangement structure,and layout of internal photovoltaic arrays.Secondly,the data characteristics of photovoltaic power output from the inverter cluster are deeply explored,and the mapping relationship between photovoltaic power and irradiance is analyzed.A virtual cloud image that describes the shape,thickness,and movement direction of cloud clusters is constructed to represent the situation of cloud obstruction(power loss).Subse-quently,a pix2pixHD image restoration algorithm of the generative adversarial network is proposed to restore the defective virtual cloud image.The algorithm integrates the most recent 5 seconds of repaired cloud images to improve the accurate representation of cloud cluster properties.Finally,based on the linear relationship between photovoltaic power,irradiance,and pixel values of virtual cloud images,high-precision photovoltaic power forecasting at the second level is achieved.An actual photovoltaic power station in a city in Shandong is taken as an example,and simulation results indi-cate that the proposed pix2pixHD image restoration forecasting model effectively enhances the accuracy of second-level photovoltaic power forecasting.
second level photovoltaic power forecastingvirtual cloud imagepix2pixHDimage inpaintingcloud oc-clusiondeep learning