Reski Khelifi

Solar stills offer a sustainable solution to water scarcity, especially in arid and remote regions. Among various configurations, pyramid‐shaped solar stills exhibit superior performance over traditional basin‐type designs, attributable to their augmented condensing surfaces and multifaceted orientations that optimize solar irradiance capture. This study aims to experimentally enhance the performance of a pyramid solar still by integrating naturally sourced gravel and volcanic pebbles as sensible thermal energy storage media. Experimental trials were conducted under the hyper‐arid climatic conditions of Ghardaïa, Algeria. The primary objective was to quantify the improvements in freshwater productivity and thermal efficiency achieved using these economical, regionally abundant, and low‐cost materials. The volcanic pebble configuration yielded the paramount outcomes, with a distillate production that was 75% higher than that of the conventional pyramid solar still. Under direct natural irradiation the pyramid solar still equipped with volcanic pebbles, reached 30.79°C for the natural gravel configuration still. The thermal efficiency of the volcanic pebble‐based pyramidal solar still reached 90%, markedly surpassing the natural pebbles system's efficiency of 62%. This superior performance is attributed to the mineral‐rich architecture of the volcanic pebbles, which improves solar energy absorption and thermal heat retention. Furthermore, the pyramidal solar still design proved cost‐effective, with a cost per liter of 0.0285 USD/L for the pyramid solar still with pebble integrated variant and 0.0494 USD/L for the conventional pyramid solar still.

Remote agricultural regions in desert areas, such as Ghardaïa in southern Algeria, face significant challenges in energy supply due to their isolated locations and harsh climatic conditions. Harnessing solar energy through photovoltaic (PV) systems offers a sustainable solution to these energy needs. This study aims to identify suitable areas for PV power installations in Ghardaïa, utilizing a geographic information system (GIS) combined with the fuzzy analytical hierarchy process (AHP). Various environmental, economic, and technical factors, such as solar radiation, land use, and proximity to infrastructure, are incorporated into the analysis to create a multi-criteria decision-making framework. The integration of fuzzy logic into AHP enables a more flexible evaluation of these factors. The results revealed the presence of ideal locations for installing photovoltaic stations, with 346,673.30 hectares identified as highly suitable, 977,606.84 hectares as very suitable, and 937,385.97 hectares as suitable. These areas are characterized by high levels of solar radiation and suitable infrastructure availability, contributing to reduced implementation costs and facilitating logistical operations. Additionally, the proximity of these locations to agricultural areas enhances the efficiency of electricity delivery to farmers. The study emphasizes the need for well-considered strategic planning to achieve sustainable development in remote rural areas.

This paper discusses the efficient implementation of a new hybrid approach to forecasting short-term PV power production for four different PV plants in Algeria. The developed model incorporates a time-varying filter-empirical mode decomposition (TVF-EMD) and an extreme learning machine (ELM) as an essence regression. The TVF-EMD technique is used to deal with the fluctuation of PV power data by splitting it into a series of more stable and constant subseries. The specified set of features (intrinsic mode functions (IMFs)) is utilized for training and improving our forecasting extreme learning machine model. The adjusted ELM model is used to evaluate prediction efficiency. The suggested TVF-EMD-ELM model is assessed and verified in various Algerian locations with varying climate conditions. In all examined regions, the TVF-EMD-ELM model generates less than 4% error in terms of normalized root mean square error (nRMSE).