Modified differential evolution approaches applied in exergoeconomic analysis and optimization of a cogeneration system
► In this study a cogeneration system is optimized using exergoeconomic principles. ► Modified diferential evolution approaches were proposed to solve the problem optimization. ► In this study we conclude that the minimum cost of 1272 ($/h) was obtained with MDE(3) while MDE(5) presented the minor C...
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| Published in | Expert systems with applications Vol. 38; no. 11; pp. 13886 - 13893 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.10.2011
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0957-4174 1873-6793 |
| DOI | 10.1016/j.eswa.2011.04.194 |
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| Abstract | ► In this study a cogeneration system is optimized using exergoeconomic principles. ► Modified diferential evolution approaches were proposed to solve the problem optimization. ► In this study we conclude that the minimum cost of 1272 ($/h) was obtained with MDE(3) while MDE(5) presented the minor CPU time (s). ► The properties obtained in this study are better than that obtained in previous works.
Exergoeconomic analysis and optimization technique combine second law analysis with economics for cost effective thermal systems design. Most of the conventional exergoeconomic optimization methods are iterative in nature and require the interpretation of the designer. On the other hand, as an alternative to the conventional mathematical approaches, modern stochastic optimization techniques based on evolutionary algorithms (EAs) have been given attention by researchers due to their ability to find potential solutions. A powerful EA is the differential evolution (DE) algorithm. The DE algorithm has been used in many practical cases and has demonstrated good convergence properties. In this work, a cogeneration system is optimized using exergoeconomic principles and modified DE (MDE) approaches. Results shows that the minimum cost was obtained with MDE(3) having the minimum cost of 1272.23 ($/h) while MDE(5) presents the minor CPU mean time (s). It is possible to note that the properties obtained in this study are better than that obtained in previous study, exception that the increase in capital investment cost is higher at 14.9% in comparison to 10% in the previous study, nevertheless additional investment can be paid back in approximately 3 years. |
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| AbstractList | ► In this study a cogeneration system is optimized using exergoeconomic principles. ► Modified diferential evolution approaches were proposed to solve the problem optimization. ► In this study we conclude that the minimum cost of 1272 ($/h) was obtained with MDE(3) while MDE(5) presented the minor CPU time (s). ► The properties obtained in this study are better than that obtained in previous works.
Exergoeconomic analysis and optimization technique combine second law analysis with economics for cost effective thermal systems design. Most of the conventional exergoeconomic optimization methods are iterative in nature and require the interpretation of the designer. On the other hand, as an alternative to the conventional mathematical approaches, modern stochastic optimization techniques based on evolutionary algorithms (EAs) have been given attention by researchers due to their ability to find potential solutions. A powerful EA is the differential evolution (DE) algorithm. The DE algorithm has been used in many practical cases and has demonstrated good convergence properties. In this work, a cogeneration system is optimized using exergoeconomic principles and modified DE (MDE) approaches. Results shows that the minimum cost was obtained with MDE(3) having the minimum cost of 1272.23 ($/h) while MDE(5) presents the minor CPU mean time (s). It is possible to note that the properties obtained in this study are better than that obtained in previous study, exception that the increase in capital investment cost is higher at 14.9% in comparison to 10% in the previous study, nevertheless additional investment can be paid back in approximately 3 years. Exergoeconomic analysis and optimization technique combine second law analysis with economics for cost effective thermal systems design. Most of the conventional exergoeconomic optimization methods are iterative in nature and require the interpretation of the designer. On the other hand, as an alternative to the conventional mathematical approaches, modern stochastic optimization techniques based on evolutionary algorithms (EAs) have been given attention by researchers due to their ability to find potential solutions. A powerful EA is the differential evolution (DE) algorithm. The de algorithm has been used in many practical cases and has demonstrated good convergence properties. In this work, a cogeneration system is optimized using exergoeconomic principles and modified de (MDE) approaches. Results shows that the minimum cost was obtained with MDE(3) having the minimum cost of 1272.23 ($/h) while MDE(5) presents the minor CPU mean time (s). It is possible to note that the properties obtained in this study are better than that obtained in previous study, exception that the increase in capital investment cost is higher at 14.9% in comparison to 10% in the previous study, nevertheless additional investment can be paid back in approximately 3 years. |
| Author | Sahoo, P.K. Mariani, Viviana Cocco Coelho, Leandro dos Santos |
| Author_xml | – sequence: 1 givenname: Viviana Cocco surname: Mariani fullname: Mariani, Viviana Cocco email: viviana.mariani@pucpr.br organization: Department of Mechanical Engineering, Pontifícia Universidade Católica do Paraná Imaculada Conceição, 1155, Zip code 80215-910, Curitiba, PR, Brazil – sequence: 2 givenname: Leandro dos Santos surname: Coelho fullname: Coelho, Leandro dos Santos email: leandro.coelho@pucpr.br organization: Industrial and Systems Engineering Graduate Program, Pontifícia Universidade Católica do Paraná Imaculada Conceição, 1155, Zip code 80215-910, Curitiba, PR, Brazil – sequence: 3 givenname: P.K. surname: Sahoo fullname: Sahoo, P.K. email: sahoofme@iitr.ernet.in organization: Department of Mechanical and Industrial Engineering, IIT Roorkee, Roorkee, Uttaranchal, India |
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| Cites_doi | 10.1016/j.eswa.2007.07.016 10.1016/0360-5442(94)90113-9 10.1016/S0196-8904(02)00033-X 10.1016/j.eswa.2009.11.002 10.1016/j.matcom.2009.03.005 10.1109/TPWRS.2006.873410 10.1016/S0360-5442(02)00009-9 10.1109/TEVC.2007.895272 10.1016/j.eswa.2009.06.029 10.1504/IJEX.2004.004735 10.1016/j.eswa.2009.12.045 10.1016/0360-5442(94)90116-3 10.1016/j.enbuild.2005.05.008 10.1023/A:1008202821328 10.1016/j.applthermaleng.2008.11.019 10.1016/j.enpol.2008.09.078 10.1016/j.applthermaleng.2007.10.011 10.1016/j.epsr.2006.02.013 10.1115/1.2795042 10.1016/j.chaos.2007.10.032 10.1016/j.ijrefrig.2004.09.006 10.1016/j.apenergy.2008.10.011 10.1016/0360-5442(94)90115-5 10.1016/S0196-8904(02)00032-8 10.1016/S0196-8904(02)00034-1 10.1115/1.1413463 10.1016/S0196-8904(00)00129-1 10.1016/j.enconman.2006.11.007 10.1016/j.applthermaleng.2005.09.005 10.1016/j.apenergy.2008.08.017 |
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| Keywords | Differential evolution Exergoeconomics Exergy Evolutionary algorithms Cogeneration Optimization |
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| Snippet | ► In this study a cogeneration system is optimized using exergoeconomic principles. ► Modified diferential evolution approaches were proposed to solve the... Exergoeconomic analysis and optimization technique combine second law analysis with economics for cost effective thermal systems design. Most of the... |
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| SubjectTerms | Algorithms Cogeneration Differential evolution Evolution Evolutionary algorithms Exergoeconomics Exergy Financing Investment Mathematical analysis Minimum cost Optimization |
| Title | Modified differential evolution approaches applied in exergoeconomic analysis and optimization of a cogeneration system |
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