Partial shading conditions (PSC) have negative effects on the operation of photovoltaic (PV) systems. In this paper, a PV array reconfiguration method is developed to minimize power losses of PV arrays under partial shading conditions. The proposed reconfiguration method is based on equalizing the reduction of the short-circuit current of the PV modules in the PV array. Eight state-of-the-art Convolutional Neural Network models are employed to estimate the effect of shading on the short-circuit current of a PV module. These models include LeNet-5, AlexNet, VGG 11, VGG 19, Inception V3, ResNet 18, ResNet 34, and ResNet 50. Among eight models, the VGG 19 achieves the best accuracy on 1842 sample images. Therefore, this model is used to estimate the ratio of the actual short-circuit current and the estimated short-circuit current in four studied shading scenarios. This ratio decides the switching rule between PV modules throughout the PV array under PSC. A 2×2 experimental PV array shows that the proposed reconfiguration method improves the output power from 5.81% to 25.19% in four shading patterns. Accordingly, the power losses are reduced from 1.32% to 13.75%. The power improvement and the reduction of power losses of the proposed dynamic PV array reconfiguration system under four case studies demonstrates its effectiveness in addressing the effects of PSC on the PV array.

The operation of the photovoltaic (PV) system under partial shading conditions (PSC) is complicated since the output characteristic of the PV system is profoundly affected by the heterogeneous irradiance of PSC. This paper proposes a dynamic reconfiguration framework to tackle PSC in the PV array. Continuous operation of the dynamic PV array reconfiguration under cloud-induced partial shading is considered by developing an emulator of the moving cloud. In addition, the Particle Swarm Optimization and Rao algorithms are improved to obtain the optimal PV array configuration under PSC. The operation of switching is enhanced by simultaneously considering the total switching times and the operation of highly active switches. The simulation results on the 9×9 PV array demonstrate the effectiveness of the proposed framework in terms of reducing the number of local maximum power points on the power-voltage characteristic, enhancing power output, and relieving stress on the switching operation of the PV array under different PSC.