ANN based control scheme for a three-level converter based unified power quality conditioner

Abstract

Unified power quality conditioner (UPQC) has been used convincingly to mitigate most of the electric power quality issues. Conventional control schemes such as Synchronous Reference Fame (SRF) and P-Q theory based control involves abc to/from dq/αb transformations. Hence, they involve complex calculations and require DSPs/FPGAs which are costly. Employing Artificial Intelligent control schemes helps to reduce the control system size and complexity of operation. This paper proposes an ANN controller for UPQC for effective operation and control. The ANN controller reduces the cost and complexity of the system. The controller performance is analysed under various conditions like supply voltage and load current harmonics, load unbalances, voltage sag and swell. Results prove the superiority of the ANN controller over conventional controllers. Keywords: Multilevel Inverter UPQC (MLI-UPQC), Diode clamped converter (DCC), Power quality improvement, Total Harmonic Distortion (THD), Artificial Neural Network (ANN)