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Design Optimization of a Solar-Powered Reverse Osmosis Desalination System for Small Communities

[+] Author Affiliations
Jihun Kim, Karim Hamza, Kazuhiro Saitou

University of Michigan, Ann Arbor, MI

Mohamed El Morsi, Ashraf O. Nassef

American University in Cairo, Cairo, Egypt

Sayed Metwalli

Cairo University, Cairo, Egypt

Paper No. DETC2013-12654, pp. V03AT03A020; 10 pages
  • ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 3A: 39th Design Automation Conference
  • Portland, Oregon, USA, August 4–7, 2013
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5588-1
  • Copyright © 2013 by ASME


Fresh water availability is essential for the economic development in small communities in remote areas. In desert climate, where naturally occurring fresh water is scarce, seawater or brackish water from wells is often more abundant. Since water desalination approaches are energy intensive, a strong motivation exists for the design of cost-effective desalination systems that utilize the abundant renewable energy resource; solar energy. This paper presents an optimization model of a solar-powered reverse osmosis (RO) desalination system. RO systems rely on pumping salty water at high pressure through semi-permeable membrane modules. Under sufficient pressure, water molecules will flow through the membranes, leaving salt ions behind, and are collected in a fresh water stream. Since RO system are primarily powered via electricity, the system model incorporates photovoltaic (PV) panels, and battery storage for smoothing out fluctuations in the PV power output, as well as allowing system operation for a number of hours after sunset. Design variables include sizing of the PV solar collectors, battery storage capacity, as well as the sizing of the RO system membrane module and power elements. The objective is to minimize the cost of unit volume produced fresh water, subject to constraints on production capacity. A genetic algorithm is used to generate and compare optimal designs for two different locations near the Red Sea and Sinai.

Copyright © 2013 by ASME



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