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Optimizing the Design of PV Solar Reverse Osmosis Unit (RO/PV) by using Genetic Algorithms for Abu Dhabi Climate

K. Bououni1, T. Jaber1, S. Elbehissy1

ALHOSN UNIVERSITY UAE

Fluid Dynamics & Materials Processing 2017, 13(2), 127-141. https://doi.org/10.3970/fdmp.2017.013.127

Abstract

The economic progress in the United Arab Emirates (UAE) induces to a significant increase in the demand for agricultural development. In Emirates the majority of the farms are irrigated by underground water, characterized by a high level of salinity. Liwa, Al Ain and Al Khatem areas are suffering from high water well salinity that exceeds 20,000 ppm. This work focuses on this problem and suggests a suitable solution allowing the use of renewable energy (Solar Photovoltaic) to drive RO desalination units. An optimal design of RO/PV unit adapted to a typical farm in Abu Dhabi was suggested using a model developed by using the software ROSA and HOMER. One of the main important results given by ROSA, besides the characteristics of the RO plant, is the required power to drive the plant. This data is the main input in the second part of the present work which is the design of the PV solar system. Finally, an economic and environmental study was carried to estimate the total cost of the project.

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APA Style
Bououni, K., Jaber, T., Elbehissy, S. (2017). Optimizing the design of PV solar reverse osmosis unit (RO/PV) by using genetic algorithms for abu dhabi climate. Fluid Dynamics & Materials Processing, 13(2), 127-141. https://doi.org/10.3970/fdmp.2017.013.127
Vancouver Style
Bououni K, Jaber T, Elbehissy S. Optimizing the design of PV solar reverse osmosis unit (RO/PV) by using genetic algorithms for abu dhabi climate. Fluid Dyn Mater Proc. 2017;13(2):127-141 https://doi.org/10.3970/fdmp.2017.013.127
IEEE Style
K. Bououni, T. Jaber, and S. Elbehissy, “Optimizing the Design of PV Solar Reverse Osmosis Unit (RO/PV) by using Genetic Algorithms for Abu Dhabi Climate,” Fluid Dyn. Mater. Proc., vol. 13, no. 2, pp. 127-141, 2017. https://doi.org/10.3970/fdmp.2017.013.127



cc Copyright © 2017 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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