Paper Title
Artificial Neural Network based Design and Performance of Three-Phase Solar PV Integrated UPQC
Abstract
This paper deals with the Artificial Neural Network based design and the performance analysis of the three-phase
solar photovoltaic integrated with unified power quality conditioner (PV-UPQC).It consist of the series voltage compensator
and the shunt voltage compensator, both these compensators are connected back to back with a common DC-link. The shunt
compensator extracts the power from PV array and also compensates the load current harmonics. To improve the
performance of the PV-UPQC moving average filter is used to extract the load active current component based on the
improved synchronous reference frame control. The grid side power quality problems of voltage swell and voltage sag are
compensated with the help of series compensator. During the power quality problems such as voltage sag and swell
condition the compensator injects voltage in-phase/out of phase respectively with point of common coupling (PCC). This
proposed system leads to the combination of both the benefits of improvement in the power quality as well as clean energy
generation. The dynamic performance as well as the steady state performance is evaluated by simulating in the MATLABSimulink.
Keywords - Artificial Neural Network, Series compensator, shunt compensator, Solar PV, UPQC, Power Quality, MPPT.