Power quality enhancement in grid-connected photovoltaic systems under low irradiance conditions using hybrid filters and ANN-based MPPT controllers

Abstract

Fluctuations in solar irradiance have a pronounced effect on the power quality of grid-connected photovoltaic (PV) systems. In low irradiance conditions, excessive Total Harmonic Distortion (THD) may occur, potentially triggering system disconnection when the Institute of Electrical and Electronics Engineers 5% limit is exceeded. In this context, the main objective of this paper is to enhance the injected power quality using a combination of L-filter and parallel active filter controlled by Sliding Mode Control (SMC). The effectiveness of the SMC is evaluated through a comparative study using the Hysteresis and Proportional Resonant controllers, based on the THD of the injected current. Furthermore, to minimize the output power fluctuations and thereby reduce the THD of the injected current, an artificial neural network-based maximum power point tracking approach is implemented, demonstrating improved stability, faster dynamic response, and reduced tracking error compared to conventional Perturb and Observe and incremental conductance methods. Thus, the proposed solution enhances the power quality and allows one to reduce the frequency of PV inverter disconnections under low irradiance conditions.