Experimental Study of the Cloud Influence on PV Grid Connected System

Abstract

In recent years, PV panels witnessed a vigorous gross, as their performance and the leverage of large-scale industrial production steadily decreased costs. Factors such as solar irradiance, insolation, mismatch of modules/arrays characteristic, aging, partial shading situation have a major effect on the harvested power. Evidence suggests that partial shading situation is the most critical factor and causes a significant reduction in PV system output. In this paper, a method based on two degrees of freedom, namely upper and lower was proposed in order to address the partial shading losses that due to cloud movement. Moreover, an extensive simulation of voltage, current indicators, bypassed modules, fault string, and DC output power was presented to analyze the PV system. The validation of experimental data analysis was carried out on two different days with different amounts of solar irradiance in Minqin County, Gansu Province, China. The results indicated that the power losses were 18.989 W and 127.629 W according to the minimum and the maximum irradiations

Deep reinforcement learning approach for MPPT control of partially shaded PV systems in Smart Grids

“…In the case of an MPPT control problem an action is considered as a change of the output voltage to affect the produced PV power. However, PV systems suffer from nonlinearity between the output voltage and current especially under partially shaded conditions (PSC), which can result in significant losses to the PV output power [7,8]. When PV modules belonging to the same string experience different insolation, the resulting power-voltage (P-V) relation becomes more complex and exhibits multiple peaks.…”