The improvement of power quality is critical for extending the life and efficiency of power electronics equipment in a utility distribution system. In this paper, we propose a photovoltaic integrated unified power quality conditioner (PV-UPQC) with cascaded multilevel inverter configuration based on an Artificial Neural Network (ANN) approach to improve power quality..Among the proposed methods, there is no need to use a transformer and filter when multilevel UPQC is applied and it is applied and is one of its advantages. The proposed UQPC offers a PV array composition with a power converter connected to a DC-link capacitor that can compensate for voltage sag, swell, voltage interruption, harmonics and reactive power. Robust Resilient Back Propagation Neural Network controllers are used to generate the UPQC's gating pulses. The controller's reference currents and voltages are calculated using the Synchronous Reference Frame (SRF) theory.The proposed cascaded multi-level inverter-based UPQC is designed using Matlab/Simulink Software. When compared to existing ANFIS and fuzzy logic methods, the simulation results show that the suggested method produces good results. A real-time hardware system is also set up to verify the proposed UPQC's simulation results.

Keywords : Power Quality, ANN,DG, UPQC, Powerelectronics, RBPN, SAPF