Genetic Algorithm Based PV Array Reconfiguration for Improving Power Output under Partial Shadings

Abstract

The behavior of the Photovoltaic (PV) system may change with respect to climatic conditions. Partial shading is a significant one, the most prominent one, and the problem has been worked out so far in the literature. The impact of partial shading demolishes the PV power output and manifests multiple peak points in the PV characteristics. One of the most effective techniques suggested in the literature to overcome this issue is the electrical array reconfiguration. This paper proposed an electrical array reconfiguration method based on Genetic Algorithm (GA) for Total-Cross-Tied (TCT) array to minimize PSCs and increase power production. The physical positions of the modules in the TCT array are constant in this work, but their electrical connections are altered depending on levels of irradiance. The proposed algorithm produces a TCT array connection pattern, thus spreading shading effects over the array, and increasing the power output. This method is tested under different shading conditions on 6×6 size of array and compared with existing reconfiguration methods. The performance of the proposed method is also investigated through Shadow Loss (SL), Fill-Factor (FF), and Efficiency estimation.