With the rapid advancement of the technology, a 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 for proposed deep-learning approach (DL- Approach) algorithm by using its own mathematical equations. Three subnets for active and other three for reactive weight component are used to extract the fundamental component of the load current. These updated weights are utilized for generation of the reference source currents for VSC. Hysteresis current controller (HCC) are employed in each phase in which generated switching signals pattern need to be carried out from both predicted reference source current and actual source current. As a result, the proposed technique achieves a better dynamic performance, less computation burden and better estimation speed. Consequently, the results were obtained for the different loading condition using MATLAB/Simulink software. Finally, the feasibility effectively as per the benchmark of IEEE guidelines in response to harmonics curtailment, power factor (p.f) improvement, load balancing, and voltage regulation etc.