Performance enhancement of a three-phase grid-connected PV inverter system using fractional-order integral sliding mode controls

Abstract

Grid-integrated photovoltaic (PV) systems hold significant promise for sustainable energy production. However, these systems often struggle with maintaining energy quality and stability in the face of fluctuating conditions. To address these challenges, this study proposes the use of fractional-order integral sliding mode control (FO-ISMC) for grid-connected PV systems. The system comprises solar panel arrays, a DC/DC boost converter with its controller, and a three-phase inverter integrated into the utility grid. The primary goals of this study are to maximize power extraction from the PV system and to regulate system currents, thereby improving effectiveness and power quality. The proposed method is further refined using the particle swarm optimization (PSO) algorithm to fine-tune parameter settings. By optimizing the command gains of the FOI-SMC, the PSO algorithm enhances system performance and stability. Leveraging fractional-order and integral terms provides the control signal with additional degrees of freedom, enhancing system performance in the presence of internal and external disturbances. Simulation results demonstrate the effectiveness of the proposed controller compared to the classical controller, where in the case of Irradiation taking the value of 500 W/m2, the proposed strategy reduced the values of constant voltage, active power, and reactive power by percentages estimated at 88.18%, 90%, and 70%, respectively, compared to the traditional strategy. Also, the overshoot value of active power was reduced in all completed cases compared to the traditional strategy by percentages estimated at 53.57%, 66.66%, and 65%, respectively. The proposed strategy reduced the response time of reactive power in all cases compared to the traditional strategy by percentages estimated at 58.59%, 28.80%, and 75%, respectively. These ratios show the high performance of the proposed control in improving the characteristics of the studied system compared to traditional control based on PI control.