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• The effect of weather conditions on solar radiation is studied. • We propose six models to predict daily global solar radiation. • From temperature, we can know solar radiation at a particular point on the surface of the Earth. Under weather conditions, the relationship between solar radiation and climatology of desert region is identified. Six models of global solar radiation are selected and studied during period of four years. This paper is based on solar radiation measurements in Research Unit in Renewable Energy in Saharan Medium (URER-MS) at various weather conditions. The Studies have shown that solar radiation can be calculated in terms of ambient temperature. Consequently, from temperature measurements, we know how much solar energy is received per unit area to estimate the solar radiation available at a given point on the Earth's surface. In addition, it was concluded that the impact of dust depending on varies quality of the soil, and the obtained results show that the model (M4) presents the best performance with an R2 value of 0.87. [ABSTRACT FROM AUTHOR]

• Investigations of the occurred PV pumping failures were performed. • PV modules have been exposed to harsh Saharan environmental for up to 13 years. • A detailed visual inspection of 21 -crystalline silicon PV modules was performed. • The study provides useful lessons to construct an effective PV pumping system design. Understanding photovoltaic modules' failures and degradation modes is an essential task for improving their useful lifetime and manufacturing materials. This paper focuses on the assessment and analysis of the different PV module defects that occurred in a solar pumping system after a long period of exposure (since 2008) to a harsh (hot and dry) climate. Additional issues that have been observed in these systems are highlighted to enhance their operation and maintenance. A detailed visual inspection of 21 mono-crystalline silicon PV modules revealed that EVA discoloration and metallization (bus bar, finger) corrosion are the most prevalent defects, accounting for 100% of the total, followed by front side delamination and bubbles at 80%, and cracking in solar cells at 11.77%. [ABSTRACT FROM AUTHOR]

This work aims to improve the existing monitoring systems MS for two grid-connected PV stations GCPVS of URERMS ADRAR, to eliminate its limitations. This improvement consists of developing an MS which is used for two PV stations with different configurations. This MS contains new LabVIEW-based monitoring software for visualizing real-time measured data and evaluating GCPVS performance. In addition, it illustrates the 2D and 3D real-time relationships of PV system parameters, which allow us to understand the dynamic behavior of PV system components. This developed monitoring software synchronizes also the various data acquisition units DAU of GCPVS, allowing simultaneous data access. To perform a reliable performance analysis and a comparative study of different GCPVS based on accurate measurements, the sensor's calibration is performed with its DAU. The MS autonomy is ensured by integrating developed PV-UPS. A graphical user interface is provided for the evaluation of PV-UPS performance. [Display omitted] • Improvement of the existing monitoring of GCPVS to resolve its limitations. • New LabVIEW-based software has been developed to monitor the PV station. • Real-time display of measured data and performance evaluation indices of GCPVS. • Real-time illustration of 2D and 3D relationships of PV system parameters. • Developed PV-UPS to ensure the autonomy of power supply for new monitoring system. [ABSTRACT FROM AUTHOR]

• Performance assessment and production estimation of grid-connected PV station. • Strong relationship between weather variables and the output of the PV station. • Strong interdependence of the meteorological parameters and performance parameters. • The distinction between the different variable correlation results is a hard task. • Feature selection and PCA analysis were used as dimensional reduction techniques. • Dimensionality reduced data was used for training random forest models. Meteorological variables have an important effect on the performance of a grid-connected photovoltaic station, in this paper, the impact of meteorological variables on the 6 mWp grid-connected photovoltaic station in the desert of Adrar has been explored through performance assessment and output power forecasting. The impact of the meteorological variables on performance parameters has been investigated by performing interdependence and correlation studies. A clear interdependence between some variables has been observed, but the complete separation between each variable correlation effect has proven to be a difficult task. A combination of random forest method and pre-processing techniques namely feature selection and Principal component analysis has been developed in order to predict power production using meteorological variables as inputs. The forecasting models have been evaluated in terms of computation time, accuracy, and several statistical indicators. [ABSTRACT FROM AUTHOR]