Improved Power Quality in a Solar PV Plant Integrated Utility Grid by Employing a Novel Adaptive Current Regulator

Integration of solar photovoltaic plants into the distribution systems using various power processing units produces the harmonics that may cause malfunctioning of sensitive equipment connected to the point of common coupling. To overcome this draw-back, a novel adaptive current regulator is employed for the grid interfacing voltage source inverter. In addition, a high-gain dc–dc converter with a Kalman-based maximum power point tracking algorithm is designed to achieve the high voltage level at the common dc bus. To determine three-phase reference currents, the proposed adaptive current regulator is designed by using a recurrent neural network trained with the Hebbian least mean square weight updating algorithm. They are used to generate the three-phase compensating currents for suppressing the harmonics present in the system. The proposed method has several merits, such as better harmonic mitigation ability, adaptive behavior, improved stability, and lesser settling time, as compared with the conventional PI controller. The system performance with the proposed current control regulator is analyzed via MATLAB/Simulink. Comparative analysis via simulation platform assures the improved performance in terms of power quality, settling time, and stability of the proposed controller.

Index Terms—Hebbian least mean square (LMS), high-gain converter, Kalman-based maximum power point tracking (MPPT), power quality, proportional–integral, photovoltaic (PV) system, recurrent neural network (RNN).