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Optimization coupling RO desalination unit to renewable energy by genetic algorithms
Renewable energy sources (RES) for powering desalination processes is a promising option especially in remote and arid regions where the use of conventional energy is costly or unavailable. Reverse osmosis (RO) is one of the most suitable desalination processes to be coupled with different RES such...
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Published in: | Desalination and water treatment 2013-02, Vol.51 (7-9), p.1416-1428 |
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container_title | Desalination and water treatment |
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creator | Ben M’Barek, T. Bourouni, K. Ben Mohamed, K.B. |
description | Renewable energy sources (RES) for powering desalination processes is a promising option especially in remote and arid regions where the use of conventional energy is costly or unavailable. Reverse osmosis (RO) is one of the most suitable desalination processes to be coupled with different RES such as solar and wind. If RES/RO systems are optimally designed, some combinations can be cost effective and reliable. However, the design of such systems is complex because of uncertain renewable energy supplies, load demands, and the non-linear characteristics of some components. In such system, different scenarios can be suggested; i.e. combinations of Photovoltaic (PV) panels, type and number of batteries, type and number of turbines, etc. Therefore, it is difficult to determine the optimal configuration with classical techniques. The development of a tool to integrate all parameters involved and compare between the possible scenarios is very important. This paper presents a new model based on the genetic algorithms allowing for coupling small RO unit to RES. A particular interest is focused on the hybrid systems (PV/WIND/Batteries/RO). The objective function to minimize corresponds to the total water cost (capital cost plus operational costs). The feasible solutions (individuals in each generation) are obtained through simulations carried along a complete year. |
doi_str_mv | 10.1080/19443994.2012.714855 |
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Reverse osmosis (RO) is one of the most suitable desalination processes to be coupled with different RES such as solar and wind. If RES/RO systems are optimally designed, some combinations can be cost effective and reliable. However, the design of such systems is complex because of uncertain renewable energy supplies, load demands, and the non-linear characteristics of some components. In such system, different scenarios can be suggested; i.e. combinations of Photovoltaic (PV) panels, type and number of batteries, type and number of turbines, etc. Therefore, it is difficult to determine the optimal configuration with classical techniques. The development of a tool to integrate all parameters involved and compare between the possible scenarios is very important. This paper presents a new model based on the genetic algorithms allowing for coupling small RO unit to RES. A particular interest is focused on the hybrid systems (PV/WIND/Batteries/RO). 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The objective function to minimize corresponds to the total water cost (capital cost plus operational costs). The feasible solutions (individuals in each generation) are obtained through simulations carried along a complete year.</description><subject>Applied sciences</subject><subject>Batteries</subject><subject>Cost engineering</subject><subject>Desalination</subject><subject>Drinking water and swimming-pool water. Desalination</subject><subject>Exact sciences and technology</subject><subject>Genetic algorithms</subject><subject>Joining</subject><subject>Mathematical models</subject><subject>Modeling</subject><subject>Optimization</subject><subject>Pollution</subject><subject>Renewable energies</subject><subject>Renewable energy</subject><subject>Reverse osmosis</subject><subject>Water treatment and pollution</subject><issn>1944-3986</issn><issn>1944-3994</issn><issn>1944-3986</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNqFkE1LAzEQhhdRUNR_4CEXwUtrvje5CCJ-QaEg9RzS7GSNbHdrkir117vLVvGkc5mXmXc-eIrijOApwQpfEs0505pPKSZ0WhKuhNgrjobyhGkl93_pw-I0pVfch-Cl4PSoWMzXOazCp82ha5HrNusmtDV6mqMKku312Ni0IaPcoQgtfNhlA6gXsd6i5RbVvczBIdvUXQz5ZZVOigNvmwSnu3xcPN_dLm4eJrP5_ePN9WziOKZ5ognWXnIu6FKWFbXclg57KiqvlRbEV4xbKUBLWgpaes-IUMwy6cApCZax4-Ji3LuO3dsGUjarkBw0jW2h2yRDylJhoYSi_1sZZYpQyQYrH60udilF8GYdw8rGrSHYDMjNN3IzIDcj8n7sfHfBJmcbH23rQvqZpVL377Dh6avRBz2Z9wDRJBegdVCFCC6bqgt_H_oCF0eTrg</recordid><startdate>20130201</startdate><enddate>20130201</enddate><creator>Ben M’Barek, T.</creator><creator>Bourouni, K.</creator><creator>Ben Mohamed, K.B.</creator><general>Elsevier Inc</general><general>Desalination Publications</general><scope>6I.</scope><scope>AAFTH</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7ST</scope><scope>7TN</scope><scope>7U6</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>L.G</scope><scope>SOI</scope><scope>7SU</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>20130201</creationdate><title>Optimization coupling RO desalination unit to renewable energy by genetic algorithms</title><author>Ben M’Barek, T. ; Bourouni, K. ; Ben Mohamed, K.B.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c402t-9109f64452b67d2a4a7c0f25df98951fd34a65e9627527ff31583a36cec86ea33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Applied sciences</topic><topic>Batteries</topic><topic>Cost engineering</topic><topic>Desalination</topic><topic>Drinking water and swimming-pool water. Desalination</topic><topic>Exact sciences and technology</topic><topic>Genetic algorithms</topic><topic>Joining</topic><topic>Mathematical models</topic><topic>Modeling</topic><topic>Optimization</topic><topic>Pollution</topic><topic>Renewable energies</topic><topic>Renewable energy</topic><topic>Reverse osmosis</topic><topic>Water treatment and pollution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ben M’Barek, T.</creatorcontrib><creatorcontrib>Bourouni, K.</creatorcontrib><creatorcontrib>Ben Mohamed, K.B.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><collection>Environmental Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Desalination and water treatment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ben M’Barek, T.</au><au>Bourouni, K.</au><au>Ben Mohamed, K.B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimization coupling RO desalination unit to renewable energy by genetic algorithms</atitle><jtitle>Desalination and water treatment</jtitle><date>2013-02-01</date><risdate>2013</risdate><volume>51</volume><issue>7-9</issue><spage>1416</spage><epage>1428</epage><pages>1416-1428</pages><issn>1944-3986</issn><issn>1944-3994</issn><eissn>1944-3986</eissn><abstract>Renewable energy sources (RES) for powering desalination processes is a promising option especially in remote and arid regions where the use of conventional energy is costly or unavailable. 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subjects | Applied sciences Batteries Cost engineering Desalination Drinking water and swimming-pool water. Desalination Exact sciences and technology Genetic algorithms Joining Mathematical models Modeling Optimization Pollution Renewable energies Renewable energy Reverse osmosis Water treatment and pollution |
title | Optimization coupling RO desalination unit to renewable energy by genetic algorithms |
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