VSC-Based DSTATCOM for PQ Improvement: A Deep-Learning Approach

Abstract With the rapid advancement of technology, deep learning supported voltage source converter (VSC)-based distributed static compensator (DSTATCOM) for power quality (PQ) improvement has attracted significant interest due to its high accuracy. In this paper, six subnets are structured proposed approach (DL-Approach) algorithm by using own mathematical equations. Three active and other three reactive weight components used extract fundamental component load current. These updated weights utilised generation reference currents VSC. Hysteresis current controllers (HCCs) employed in each phase which generated switching signal patterns need be carried out from both predicted actual As a result, technique achieves better dynamic performance, less computation burden estimation speed. Consequently, results were obtained different loading conditions MATLAB/Simulink software. Finally, feasibility was effective as per benchmark IEEE guidelines response harmonics curtailment, factor (p.f) improvement, balancing regulation.