Parametric optimization of regenerative organic Rankine cycle (ORC) for low grade waste heat recovery using genetic algorithm
By using exergy efficiency as an objective function, the performances of three different organic Rankine cycles (ORCs) systems including the basic ORC (BORC) system, the single-stage regenerative ORC (SRORC) system and the double-stage regenerative ORC (DRORC) system using six different working flui...
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Veröffentlicht in: | Energy (Oxford) 2013-09, Vol.58, p.473-482 |
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creator | Xi, Huan Li, Ming-Jia Xu, Chao He, Ya-Ling |
description | By using exergy efficiency as an objective function, the performances of three different organic Rankine cycles (ORCs) systems including the basic ORC (BORC) system, the single-stage regenerative ORC (SRORC) system and the double-stage regenerative ORC (DRORC) system using six different working fluids under the same waste heat condition are examined. The genetic algorithm (GA) is chosen as a novel way to determine the optimal fractions of the flow rates in regenerative ORC systems. The ORC systems using each working fluid are optimized to their optimal operating conditions and the corresponding thermodynamic parameters under every optimal operating condition are calculated. The results show that for each working fluid, the DRORC system always gives the best thermal efficiency and exergy efficiency under the optimal operating conditions, followed by the SRORC system, and the BORC system has the worst efficiencies. R11 and R141b are recommended as suitable working fluids for ORC systems for their superior thermodynamic performances.
•The genetic algorithm (GA) is successfully applied for optimizing ORCs.•Optimized calculations toward fractions of the flow rate are performed using GA.•The R11 and R141b, as the high-efficiency working fluids, are selected for ORCs.•The regenerative ORCs perform better than that without regenerative processes. |
doi_str_mv | 10.1016/j.energy.2013.06.039 |
format | Article |
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•The genetic algorithm (GA) is successfully applied for optimizing ORCs.•Optimized calculations toward fractions of the flow rate are performed using GA.•The R11 and R141b, as the high-efficiency working fluids, are selected for ORCs.•The regenerative ORCs perform better than that without regenerative processes.</description><identifier>ISSN: 0360-5442</identifier><identifier>DOI: 10.1016/j.energy.2013.06.039</identifier><identifier>CODEN: ENEYDS</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Applied sciences ; Computational efficiency ; Computing time ; Energy ; Exact sciences and technology ; Exergy ; Exergy efficiency ; Genetic algorithm (GA) ; Genetic algorithms ; Heat recovery ; Optimization ; Rankine cycle ; Regenerative ; Regenerative organic Rankine cycle ; Thermodynamics ; Working fluids</subject><ispartof>Energy (Oxford), 2013-09, Vol.58, p.473-482</ispartof><rights>2013 Elsevier Ltd</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c402t-4dc6068199d91890658bc0b008accf93a360f90a4a478c7e629141b77be8d423</citedby><cites>FETCH-LOGICAL-c402t-4dc6068199d91890658bc0b008accf93a360f90a4a478c7e629141b77be8d423</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.energy.2013.06.039$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27636963$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Xi, Huan</creatorcontrib><creatorcontrib>Li, Ming-Jia</creatorcontrib><creatorcontrib>Xu, Chao</creatorcontrib><creatorcontrib>He, Ya-Ling</creatorcontrib><title>Parametric optimization of regenerative organic Rankine cycle (ORC) for low grade waste heat recovery using genetic algorithm</title><title>Energy (Oxford)</title><description>By using exergy efficiency as an objective function, the performances of three different organic Rankine cycles (ORCs) systems including the basic ORC (BORC) system, the single-stage regenerative ORC (SRORC) system and the double-stage regenerative ORC (DRORC) system using six different working fluids under the same waste heat condition are examined. The genetic algorithm (GA) is chosen as a novel way to determine the optimal fractions of the flow rates in regenerative ORC systems. The ORC systems using each working fluid are optimized to their optimal operating conditions and the corresponding thermodynamic parameters under every optimal operating condition are calculated. The results show that for each working fluid, the DRORC system always gives the best thermal efficiency and exergy efficiency under the optimal operating conditions, followed by the SRORC system, and the BORC system has the worst efficiencies. R11 and R141b are recommended as suitable working fluids for ORC systems for their superior thermodynamic performances.
•The genetic algorithm (GA) is successfully applied for optimizing ORCs.•Optimized calculations toward fractions of the flow rate are performed using GA.•The R11 and R141b, as the high-efficiency working fluids, are selected for ORCs.•The regenerative ORCs perform better than that without regenerative processes.</description><subject>Applied sciences</subject><subject>Computational efficiency</subject><subject>Computing time</subject><subject>Energy</subject><subject>Exact sciences and technology</subject><subject>Exergy</subject><subject>Exergy efficiency</subject><subject>Genetic algorithm (GA)</subject><subject>Genetic algorithms</subject><subject>Heat recovery</subject><subject>Optimization</subject><subject>Rankine cycle</subject><subject>Regenerative</subject><subject>Regenerative organic Rankine cycle</subject><subject>Thermodynamics</subject><subject>Working fluids</subject><issn>0360-5442</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNqFkcFq3DAQhn1IIek2b9CDLoH0sM7IlmXrUihL0wYCKSF3MSuPHW1taStpN2yh715tN_TYooMQfPMN-v-ieM-h5MDlzaYkR2E8lBXwugRZQq3OiguoJSwbIarz4m2MGwBoOqUuil_fMOBMKVjD_DbZ2f7EZL1jfmCBxqMrv_fEfBjRZegR3XfriJmDmYhdPzyuPrDBBzb5FzYG7Im9YEzEnglTNhi_p3Bgu2jdyI66lB04jT7Y9Dy_K94MOEW6fL0XxdPt56fV1-X9w5e71af7pRFQpaXojQTZcaV6xTsFsunWBtYAHRozqBrz5wYFKFC0nWlJVooLvm7bNXW9qOpFcX3SboP_saOY9GyjoWlCR34XNW94Lao2x_d_VEjRyFrlsyjECTXBxxho0NtgZwwHzUEfu9AbfepCH7vQIDX8Gbt63YDR4DQEdMbGv7NVK2upZJ25jyeOcjB7S0FHY8kZ6m2ONene238v-g0ldKRX</recordid><startdate>20130901</startdate><enddate>20130901</enddate><creator>Xi, Huan</creator><creator>Li, Ming-Jia</creator><creator>Xu, Chao</creator><creator>He, Ya-Ling</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20130901</creationdate><title>Parametric optimization of regenerative organic Rankine cycle (ORC) for low grade waste heat recovery using genetic algorithm</title><author>Xi, Huan ; Li, Ming-Jia ; Xu, Chao ; He, Ya-Ling</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c402t-4dc6068199d91890658bc0b008accf93a360f90a4a478c7e629141b77be8d423</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Applied sciences</topic><topic>Computational efficiency</topic><topic>Computing time</topic><topic>Energy</topic><topic>Exact sciences and technology</topic><topic>Exergy</topic><topic>Exergy efficiency</topic><topic>Genetic algorithm (GA)</topic><topic>Genetic algorithms</topic><topic>Heat recovery</topic><topic>Optimization</topic><topic>Rankine cycle</topic><topic>Regenerative</topic><topic>Regenerative organic Rankine cycle</topic><topic>Thermodynamics</topic><topic>Working fluids</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xi, Huan</creatorcontrib><creatorcontrib>Li, Ming-Jia</creatorcontrib><creatorcontrib>Xu, Chao</creatorcontrib><creatorcontrib>He, Ya-Ling</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Energy (Oxford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xi, Huan</au><au>Li, Ming-Jia</au><au>Xu, Chao</au><au>He, Ya-Ling</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Parametric optimization of regenerative organic Rankine cycle (ORC) for low grade waste heat recovery using genetic algorithm</atitle><jtitle>Energy (Oxford)</jtitle><date>2013-09-01</date><risdate>2013</risdate><volume>58</volume><spage>473</spage><epage>482</epage><pages>473-482</pages><issn>0360-5442</issn><coden>ENEYDS</coden><abstract>By using exergy efficiency as an objective function, the performances of three different organic Rankine cycles (ORCs) systems including the basic ORC (BORC) system, the single-stage regenerative ORC (SRORC) system and the double-stage regenerative ORC (DRORC) system using six different working fluids under the same waste heat condition are examined. The genetic algorithm (GA) is chosen as a novel way to determine the optimal fractions of the flow rates in regenerative ORC systems. The ORC systems using each working fluid are optimized to their optimal operating conditions and the corresponding thermodynamic parameters under every optimal operating condition are calculated. The results show that for each working fluid, the DRORC system always gives the best thermal efficiency and exergy efficiency under the optimal operating conditions, followed by the SRORC system, and the BORC system has the worst efficiencies. R11 and R141b are recommended as suitable working fluids for ORC systems for their superior thermodynamic performances.
•The genetic algorithm (GA) is successfully applied for optimizing ORCs.•Optimized calculations toward fractions of the flow rate are performed using GA.•The R11 and R141b, as the high-efficiency working fluids, are selected for ORCs.•The regenerative ORCs perform better than that without regenerative processes.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.energy.2013.06.039</doi><tpages>10</tpages></addata></record> |
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subjects | Applied sciences Computational efficiency Computing time Energy Exact sciences and technology Exergy Exergy efficiency Genetic algorithm (GA) Genetic algorithms Heat recovery Optimization Rankine cycle Regenerative Regenerative organic Rankine cycle Thermodynamics Working fluids |
title | Parametric optimization of regenerative organic Rankine cycle (ORC) for low grade waste heat recovery using genetic algorithm |
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