Application of Lightweight Image Super-Resolution Technology in Smart Grid Management System

To improve the efficiency of smart grid management system and meet the requirements of real-time operation of power grid lines, we propose a lightweight adaptive weighted attention network (AWAN) for smart grid system. Specifically, a novel lightweight adaptive weighted attention block (AWAB) is carefully designed as the fundamental block. AWAB is actually a multi-branch block, which is made up of linear feature extraction block (LFEB), lightweight channel attention block (LCAB), and nonlinear block (LNB). With these three branches, AWAB can effectively extract discriminative feature and assign more weight to the high-frequency information. The qualitative and quantitative experiments have validated that AWAN can rebuilt better HR images for image super-resolution compared with lightweight method, i.e., SRCNN, FSRCNN, VDSR, and DRCN.