Multiobjective genetic algorithm strategies for electricity production from generation IV nuclear technology
Development of a technico-economic optimization strategy of cogeneration systems of electricity/hydrogen, consists in finding an optimal efficiency of the generating cycle and heat delivery system, maximizing the energy production and minimizing the production costs. The first part of the paper is r...
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Veröffentlicht in: | Energy conversion and management 2010-04, Vol.51 (4), p.859-871 |
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creator | Gomez, Adrien Pibouleau, Luc Azzaro-Pantel, Catherine Domenech, Serge Latgé, Christian Haubensack, David |
description | Development of a technico-economic optimization strategy of cogeneration systems of electricity/hydrogen, consists in finding an optimal efficiency of the generating cycle and heat delivery system, maximizing the energy production and minimizing the production costs. The first part of the paper is related to the development of a multiobjective optimization library (MULTIGEN) to tackle all types of problems arising from cogeneration. After a literature review for identifying the most efficient methods, the MULTIGEN library is described, and the innovative points are listed. A new stopping criterion, based on the stagnation of the Pareto front, may lead to significant decrease of computational times, particularly in the case of problems involving only integer variables. Two practical examples are presented in the last section. The former is devoted to a bicriteria optimization of both exergy destruction and total cost of the plant, for a generating cycle coupled with a Very High Temperature Reactor (VHTR). The second example consists in designing the heat exchanger of the generating turbomachine. Three criteria are optimized: the exchange surface, the exergy destruction and the number of exchange modules. |
doi_str_mv | 10.1016/j.enconman.2009.11.022 |
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Three criteria are optimized: the exchange surface, the exergy destruction and the number of exchange modules.</description><identifier>ISSN: 0196-8904</identifier><identifier>EISSN: 1879-2227</identifier><identifier>DOI: 10.1016/j.enconman.2009.11.022</identifier><identifier>CODEN: ECMADL</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Alternative fuels. Production and utilization ; Applied sciences ; Chemical and Process Engineering ; Chemical engineering ; Chemical Sciences ; Cogeneration ; Cogeneration electricity/hydrogen ; Criteria ; Destruction ; Economic data ; Electric energy ; Electricity ; Energy ; Energy economics ; Energy. Thermal use of fuels ; Engineering Sciences ; Exact sciences and technology ; Exergy ; Fission nuclear power plants ; Fuels ; General, economic and professional studies ; Genetic algorithm ; Hydrogen ; Installations for energy generation and conversion: thermal and electrical energy ; Mathematical analysis ; Mathematical models ; Multiobjective optimization ; Nuclear technology ; Optimization</subject><ispartof>Energy conversion and management, 2010-04, Vol.51 (4), p.859-871</ispartof><rights>2009 Elsevier Ltd</rights><rights>2015 INIST-CNRS</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c489t-fbd18e31b2a8196c083cf0b4ca514f59c75b3b86798ab543f27011e66316d693</citedby><cites>FETCH-LOGICAL-c489t-fbd18e31b2a8196c083cf0b4ca514f59c75b3b86798ab543f27011e66316d693</cites><orcidid>0000-0001-5832-5199</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0196890409004671$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=22516490$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-03549569$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Gomez, Adrien</creatorcontrib><creatorcontrib>Pibouleau, Luc</creatorcontrib><creatorcontrib>Azzaro-Pantel, Catherine</creatorcontrib><creatorcontrib>Domenech, Serge</creatorcontrib><creatorcontrib>Latgé, Christian</creatorcontrib><creatorcontrib>Haubensack, David</creatorcontrib><title>Multiobjective genetic algorithm strategies for electricity production from generation IV nuclear technology</title><title>Energy conversion and management</title><description>Development of a technico-economic optimization strategy of cogeneration systems of electricity/hydrogen, consists in finding an optimal efficiency of the generating cycle and heat delivery system, maximizing the energy production and minimizing the production costs. The first part of the paper is related to the development of a multiobjective optimization library (MULTIGEN) to tackle all types of problems arising from cogeneration. After a literature review for identifying the most efficient methods, the MULTIGEN library is described, and the innovative points are listed. A new stopping criterion, based on the stagnation of the Pareto front, may lead to significant decrease of computational times, particularly in the case of problems involving only integer variables. Two practical examples are presented in the last section. The former is devoted to a bicriteria optimization of both exergy destruction and total cost of the plant, for a generating cycle coupled with a Very High Temperature Reactor (VHTR). The second example consists in designing the heat exchanger of the generating turbomachine. Three criteria are optimized: the exchange surface, the exergy destruction and the number of exchange modules.</description><subject>Alternative fuels. Production and utilization</subject><subject>Applied sciences</subject><subject>Chemical and Process Engineering</subject><subject>Chemical engineering</subject><subject>Chemical Sciences</subject><subject>Cogeneration</subject><subject>Cogeneration electricity/hydrogen</subject><subject>Criteria</subject><subject>Destruction</subject><subject>Economic data</subject><subject>Electric energy</subject><subject>Electricity</subject><subject>Energy</subject><subject>Energy economics</subject><subject>Energy. Thermal use of fuels</subject><subject>Engineering Sciences</subject><subject>Exact sciences and technology</subject><subject>Exergy</subject><subject>Fission nuclear power plants</subject><subject>Fuels</subject><subject>General, economic and professional studies</subject><subject>Genetic algorithm</subject><subject>Hydrogen</subject><subject>Installations for energy generation and conversion: thermal and electrical energy</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Multiobjective optimization</subject><subject>Nuclear technology</subject><subject>Optimization</subject><issn>0196-8904</issn><issn>1879-2227</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><recordid>eNqFkUFv1DAQhS0EEsu2fwHlgoBDUo-TOPaNqoK20iIuVa-W40x2vXLiYjsr7b_Hy7Y9wmnk0fdm3vgR8hFoBRT41b7C2fh50nPFKJUVQEUZe0NWIDpZMsa6t2RFQfJSSNq8Jx9i3FNK65byFXE_F5es7_dokj1gscUZkzWFdlsfbNpNRUxBJ9xajMXoQ4Euk8Eam47FU_DDknV-Lsbgp7_iDJ_e94_FvBiHOhQJzW72zm-PF-TdqF3Ey-e6Jg8_vj_c3JWbX7f3N9eb0jRCpnLsBxBYQ8-0yLYNFbUZad8Y3UIzttJ0bV_3gndS6L5t6pF1FAA5r4EPXNZr8vU8dqedegp20uGovLbq7nqjTr18eyNbLg-Q2c9nNt_ye8GY1GSjQef0jH6JSgjZAJPZwpp8-ScJXddBIznwjPIzaoKPMeD46gKoOmWm9uolM3XKTAGonFkWfnreoaPRbgx6Nja-qhlrgTeSZu7bmcP8iweLQUVj80QcbMjxqMHb_636A_qMsVg</recordid><startdate>20100401</startdate><enddate>20100401</enddate><creator>Gomez, Adrien</creator><creator>Pibouleau, Luc</creator><creator>Azzaro-Pantel, Catherine</creator><creator>Domenech, Serge</creator><creator>Latgé, Christian</creator><creator>Haubensack, David</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SU</scope><scope>7TB</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>7ST</scope><scope>SOI</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0001-5832-5199</orcidid></search><sort><creationdate>20100401</creationdate><title>Multiobjective genetic algorithm strategies for electricity production from generation IV nuclear technology</title><author>Gomez, Adrien ; Pibouleau, Luc ; Azzaro-Pantel, Catherine ; Domenech, Serge ; Latgé, Christian ; Haubensack, David</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c489t-fbd18e31b2a8196c083cf0b4ca514f59c75b3b86798ab543f27011e66316d693</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Alternative fuels. 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subjects | Alternative fuels. Production and utilization Applied sciences Chemical and Process Engineering Chemical engineering Chemical Sciences Cogeneration Cogeneration electricity/hydrogen Criteria Destruction Economic data Electric energy Electricity Energy Energy economics Energy. Thermal use of fuels Engineering Sciences Exact sciences and technology Exergy Fission nuclear power plants Fuels General, economic and professional studies Genetic algorithm Hydrogen Installations for energy generation and conversion: thermal and electrical energy Mathematical analysis Mathematical models Multiobjective optimization Nuclear technology Optimization |
title | Multiobjective genetic algorithm strategies for electricity production from generation IV nuclear technology |
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