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<ArticleSet>
<Article>
<Journal>
<PublisherName>OICC Press</PublisherName>
<JournalTitle>International Journal of Energy and Environmental Engineering</JournalTitle>
<Issn>2251-6832</Issn>
<Volume>9</Volume>
<Issue>1 (March 2018)</Issue>
<PubDate PubStatus="epublish">
<Year>2017</Year>
<Month>10</Month>
<Day>26</Day>
</PubDate>
</Journal>
<ArticleTitle>Evaluation and optimization of organic Rankine cycle (ORC) with algorithms NSGA-II, MOPSO, and MOEA for eight coolant fluids</ArticleTitle>
<VernacularTitle></VernacularTitle>
<FirstPage></FirstPage>
<LastPage></LastPage>
<ELocationID EIdType="doi">10.1007/s40095-017-0251-7</ELocationID>
<Language>EN</Language>
<AuthorList>
<Author>
<FirstName>E.</FirstName>
<LastName>Ghasemian</LastName>
<Affiliation>Department of Mechanical Engineering, Pardis Branch, Islamic Azad University, Pardis New City, IR</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
<Author>
<FirstName>M. A.</FirstName>
<LastName>Ehyaei</LastName>
<Affiliation>Department of Mechanical Engineering, Pardis Branch, Islamic Azad University, Pardis New City, IR</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
</AuthorList>
<PublicationType>Journal Article</PublicationType>
<History>
<PubDate PubStatus="received">
<Year>2017</Year>
<Month>10</Month>
<Day>26</Day>
</PubDate>
</History>
<Abstract>Abstract
In this study, a simple organic cycle for eight subcritical coolant fluids has been studied thermodynamically and economically. For all the coolants, the present cycle was optimized for the best thermal and exergy efficiencies and the best cost of energy production. In a multi-purpose procedure, using the three methods NSGA-II, MOPSO, and MOEA/D, design variables in the optimization are the inlet turbine pressure and temperature, the pinch temperature difference, the proximity temperature difference in regenerator exchanger, and condenser temperature difference. The optimization results show that, in all three methods, the impact of the parameters’ inlet turbine temperature and pressure on the three objective functions is much more than other design parameters. Coolant with positive temperature gradients shows a better performance but lower produced power. In optimization methods, among all the coolants, the MOPSO method showed higher thermal and energy efficiency, and the MOEA/D showed lower production power costs. In terms of the rate of convergence, also both the MOPSO and NSGA-II methods showed better performance. The fluid R
11
 with the 25.7% thermal efficiency, 57.3% exergy efficiency, and 0.054 USD cost per kWh showed the best performance among all of the coolants.</Abstract>
<ObjectList>
<Object Type="keyword">
<Param Name="value">Optimization</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Organic Rankine cycle</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Coolant fluid</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Exergy</Param>
</Object>
</ObjectList>
</Article>
</ArticleSet>