Noureddine Benabadji

The main objective of this study is to evaluate the performance of a photovoltaic (PV) system under real-world conditions by analyzing three key climatic variables on a monthly scale: insolation, average daily temperature, and photovoltaic power output. Insolation, defined as the average daily sunshine duration, is a critical parameter for estimating the solar energy potential in the Ghardaïa region, which is characterized by a desert climate. Average daily temperature directly influences the efficiency of PV panels, as elevated temperatures tend to reduce their performance. Photovoltaic power output, expressed in kWh/m²/day, is calculated based on solar radiation, providing a measure of actual energy generation under prevailing climate conditions. The analysis of these three climatic parameters offers valuable insights into seasonal variations and their impact on solar energy production in the Ghardaïa region. To optimize PV system performance, the study emphasizes the importance of accurate system design supported by advanced numerical methods. We extend the modeling from individual solar cells to complete PV modules and arrays, accurately reproducing their electrical characteristics. Simulations are performed in MATLAB/Simulink to validate the proposed model, which is based on an enhanced two-diode representation that reflects realistic operating conditions.

Climate change has been a significant international issue for several years. As humanity continues to experience its effects, this issue will only become more pressing. The trend suggests a long-term increase in global temperatures driven by record levels of heat-trapping greenhouse gases (GHG) in the atmosphere. The most significant of these gases is carbon dioxide (CO2), which has the greatest impact on the greenhouse effect. It is crucial to monitor CO2 concentrations in the atmosphere to evaluate the effectiveness of efforts to reduce GHG emissions and to identify any unusual increases. Images from the OCO-2 (Orbiting Carbon Observatory 2) satellite provide XCO2 data since 2014. Initially, this information is combined with measurements of CO2 concentrations on the ground recorded by the Assekrem station located in southern Algeria in order to build a model that can be applied to the Oran region. The performance of the model is characterized by R² = 0.948, RMSE = 1.017 ppm, and MAE = 0.83 ppm. Secondly, the XCO2 data are used to estimate CO2 concentrations in the urban environment of Oran city, in peri-urban areas, and industrial environments based on the created model. The results are compared to ground measurements recorded by a CO2 analyzer equipped with MH-Z19B micro-sensor, calibrated with a classic instrument. Calibration improvements were achieved through machine learning, with MLR emerging as the most effective method (R² = 70.7%). The developed methodology is fast, cost-effective, and adaptable for use in other regions to monitor the evolution of CO2 concentrations in ambient air. The novelty of this approach lies in the combined use of satellite observations, reference-grade monitoring, and low-cost sensors within a machine learning methodology. This multi-source integration offers significant potential for improving local CO₂ estimations and for expanding validation networks, particularly in under-instrumented regions.

Amorphous silicon (a-Si) is rarely used for large scale photovoltaic energy production, it remains relevant in flexible electronic applications, where mechanical flexibility and lightweight design are prioritized, where exposure to sunlight is typically limited or irregular. This study conducts an experimental analysis of the long-term aging effects on the proprieties of an amorphous solar cells, under five years of intermittent outdoor climate conditions. Unlike conventional aging studies that focus on degradation over time, this research highlights the cumulative effects of environmental exposure, considering the discontinuous nature of exposure cycles and the non-linearity of degradation phenomena because of the abrupt transitions between outdoor exposure phases and indoor laboratory rest periods. The results show that nearly 50% of the panel’s performances is reduced, with the losses observed as follows: a substantial decline in the fill factor from 55.3% to 30%, a decrease in energy conversion efficiency from 11.36% to 5.5%. This accelerated deterioration mainly attributed to harsh environmental transitions caused by intermittent exposure, which amplify aging mechanism compared to continuous exposure. Beyond the experimental findings, the approach presented here, constitutes a meaningful scientific contribution. By introducing a realistic and underexplored aging scenario, it lays the groundwork for a new line of research.

Driven by growing electricity demand, Algeria is diversifying its energy mix with a focus on solar power. A successful transition requires robust climate analysis to guide decision makers and investments. This study investigated the influence of specific weather regimes (WRs) on Algeria’s energy sector, analyzing their summer impacts on solar production, energy demand, and the resulting energy shortfall, expressed as the daily difference between demand and potential solar generation. We further examined the occurrence of Energy Supply Droughts (ESDs), periods when this shortfall exceeds a critical threshold. It was observed that days with a negative North Atlantic Oscillation (NAO−) followed by an Atlantic Ridge (AR) generate a solar surplus and lower demand, creating ideal conditions for energy storage. Conversely, a positive North Atlantic Oscillation (NAO+) reduces production while increasing demand, frequently leading to ESD events. Although generally neutral, Scandinavian Blocking (BL) also contributes to ESDs by amplifying unfavorable energy anomalies. Notably, ESD events associated with NAO+ and BL show strong convergence with similar synoptic configurations and spatial structures. However, while WRs are useful for operational forecasting, predicting extreme ESDs requires an approach that directly targets extreme weather conditions.

The paper focuses on the design and implementation of a low cost and compact data logger prototype using an extreme low power (XLP) and low pin count programmable interface controllers (PIC) microcontroller using its own flash memory for the periodic data acquisition storage, while many other works focus in the Arduino Eco-system. It is planned to pick four important analog measures from the photovoltaic system, and store them directly as 10-bit numerical counts, this yields to faster data acquisition and storage (no time consuming for mathematical computation to convert each numerical count of raw data to meaningful real-world data). Avoiding the use of any kind of display and keypad, and keeping the ratio run time over sleep time as low as possible, has a maximum impact on lowering the power consumption. This prototype can be serially linked to a personal computer (PC) to view the acquisition of measurements in real time, and to retrieve all collected data through a terminal application. The experimental results are stored in comma-separated values (CSV) files to ease post data analysis with any spread sheet software, for statistical calculations and graphs drawing, in order for instance, to find the faults of the photovoltaic system and optimize its management and its performance.

In Algeria, the alternative to the absence of these air pollution measurement networks can come from the recent development of electrochemical sensor technologies for air quality monitoring which arouses a certain interest because of their miniaturization, low energy consumption and low cost. We developed a low-cost outdoor carbon monoxide analyzer called APOMOS (Air pollution Monitoring System) based on electrochemical sensor managed by microcontroller. In order to validate the APOMOS system, the recorded measurements are compared with measurements taken by a conventional analyzer. Comparison of the measurements resulting from conventional analyzer and those resulting from the APOMOS system gives a coefficient of determination of 98.39 %.

Over the Sahara in summer, the activity of the Saharan thermal low pressure system (SHL), which is linked to the West-African monsoon dynamics and the mid-latitude circulation, is modulated by dust concentration and water-vapor transport. In this context, the role of clouds over western Sahara remains under-investigated. Using Meteosat-Second-Generation geostationary satellite data, for the first time the variability of cloud occurrence over Sahara by type in summer, at diurnal, daily and intra-seasonal time scales for the 2008–2014 period is documented. Using European Center for Medium-range Weather Forecasting (ECMWF) Reanalysis (ERA) Interim (ERAI) reanalysis, cloud cover occurrences are characterized in terms of regional circulation patterns and moisture balance. We show that, over West-Sahara and Hoggar, mid-top clouds are the most frequent cloud-type in summer. Their summit reaches between 500 hPa and 400 hPa and lies just above the top of the Saharan Atmospheric Boundary Layer (SABL). During the rest of the year, high-top clouds are the most frequent. The variations in the spatial distribution of mid-top cloud occurrence coincide with the seasonal displacement and strengthening of the SHL and, in the mid-troposphere, of the Saharan anticyclone. Mid-top clouds occur most frequently when, at large scale, mass and humidity converge in the lower SABL due to heating on an extensive surface, and diverge in the upper SABL. Their diurnal cycle, with minimal frequency around 10 UTC and maximum in the evening, is consistent with the diurnal development of the Saharan Convective-Boundary-Layer. The frequency of high cloud increases when anticyclonic circulations at mid-level and upper-level retreat to the southeast and upper-level trough from mid-latitudes can penetrate more southwards.

Background: The effect of confinement due to the coronavirus disease 2019 (COVID-19) pandemic on air pollution has been investigated in several cities. Indeed, the concentration of the main air pollutants have decreased significantly due to the decline in activities consuming fossil fuels. However, it was found that the concentration of ...

In stand-alone photovoltaic installations the photovoltaic inverter allows transforming the DC power produced by the photovoltaic modules into an AC power. Depending on the shape of the AC output voltage generated by the inverter there exist three main types of stand-alone PV inverters: pure sine waveform inverters, modulated sine waveform inverters and square waveform inverters and each type of these inverters is also divided into different topologies. In this paper we will be interested and study the square waveform stand-alone inverter topologies which are the half bridge and the full-bridge inverter topologies.