The string segmentation task of photovoltaic power station requires to accurately identify the edge of PV string, so as to obtain accurate position information. For this task, this paper designs the scSE-Unet8 semantic segmentation model. The squeeze excitation module (SCSE) was introduced into the U-Net and the complexity of the model was reduced. The model was trained and verified on the aerial image data set of PV power station. The experimental results show that compared with the U-Net, scSE module revise the space and channel features, so as to emphasize the important edge feature information. Therefore, scSE-Unet8 has better effect on string edge pixel detection. After cross validation, the mIoU (Mean Intersection over Union) on the test set is 98.62%. The boundary information extraction algorithm was used to process the output result of scSE-Unet8, eliminate a small amount of false detection and missed detection in the original segmentation result, and the string boundary at the pixel level can be obtained.