Treffer: Year-round performance evaluation of a solar-powered compact HDH desalination system for remote water scarce regions.

Title:
Year-round performance evaluation of a solar-powered compact HDH desalination system for remote water scarce regions.
Authors:
AbdelMeguid, Hossam1,2 (AUTHOR) hssaleh@mans.edu.eg
Source:
International Journal of Green Energy. 2025, Vol. 22 Issue 11, p2223-2245. 23p.
Reviews & Products:
Database:
GreenFILE

Weitere Informationen

Climate change is intensifying global hydrological stress, increasing evaporation, degrading water quality, raising water temperatures, and altering runoff periods. This study introduces a fully solar-powered humidification-dehumidification (HDH) desalination system designed to address water scarcity in remote and arid regions. The significance of the research lies in its potential to provide a sustainable, off-grid water supply using renewable solar energy, which is particularly relevant in areas with limited infrastructure. The aim of the study is to evaluate the year-round performance of the system by developing a comprehensive mathematical model based on mass, energy, and momentum conservation equations. The model simulates the system's behavior under varying solar conditions, enabling the optimization of key parameters. The system combines thermal photovoltaic panels and evacuated tube solar water collectors, enhancing energy efficiency through the pre-heating of seawater. The model is implemented in MATLAB, and the performance is evaluated over a full annual cycle. Results show that the system achieves a peak efficiency of 42% during high solar months, with monthly productivities of up to 238.87 L/m2, while the lowest performance occurs in December, with 14% efficiency and 63.02 L/m2 productivity. These findings underscore the system's capability to provide a sustainable water source year-round. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Green Energy is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)