A Maximum Correntropy Criteria Based Adaptive Algorithm for an Improved Power Quality SPV System

Abstract

This paper presents an improved power quality solar photovoltaic (SPV) system, using a maximum correntropy criteria (MCC) based intelligent adaptive control algorithm. The proposed system is integrated into a three phase 4 wire distribution system. It feeds the active power of the solar PV (P PV ) to the loads connected at the Point of Common Coupling (PCC) and delivers the excess power (in daytime) of the solar PV array to the distribution system at unity power factor (UPF). The proposed system mitigates the power quality problems by providing the reactive power and harmonics power locally and maintains the Supply Current i s total harmonic distortion (THD) within the set limits by various international standards. In the first stage, a DC-DC converter is used to extract the PV peak power $(\mathrm {P}_{\mathrm {P}\mathrm {V}_{-}\mathrm {P}\mathrm {e}\mathrm {a}\mathrm {k}})$ to optimize the PV system. It utilized a perturb and observe (P&O) approach for peak power extraction. In the second stage, a 3 phase 4 leg voltage source converter (VSC) is used to convert the DC power into AC power. The VSC is controlled by using an MCC based adaptive control algorithm. It extracts the fundamental active component of the load current $(\mathrm {w}_{\mathrm {p}\mathrm {L}})$ from the nonlinear load current. The controller is adaptive in nature and adapts its step size parameter as the system conditions change and show a good dynamic response. The system performance is validated on a laboratory prototype in steady state and dynamic conditions.