The optimum sizing of zero-emission water-cooled VCR cycle based on exergo-economic-environmental assessment criteria by triple-objective MPSO
Abstract Renewable energies are interesting as an alternative and sustainable resource for air conditioning applications. But initial investment cost of equipment, whose employed for converting the renewable energy into usable shape and also for air conditioning duty, are significant. Therefore, det...
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Nature Portfolio
2024-11-01
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| Online Access: | https://doi.org/10.1038/s41598-024-78994-z |
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| author | Seyedeh Mohadeseh Miri Mahmood Farzaneh-Gord Alireza Hosseinpour Mohit Bajaj Ievgen Zaitsev |
| author_facet | Seyedeh Mohadeseh Miri Mahmood Farzaneh-Gord Alireza Hosseinpour Mohit Bajaj Ievgen Zaitsev |
| author_sort | Seyedeh Mohadeseh Miri |
| collection | DOAJ |
| description | Abstract Renewable energies are interesting as an alternative and sustainable resource for air conditioning applications. But initial investment cost of equipment, whose employed for converting the renewable energy into usable shape and also for air conditioning duty, are significant. Therefore, determining the optimum sizing has high priority. In current study, water cooled vapor compression refrigeration cycle powered by wind energy and storage tank is proposed, simulated and optimized. To contribute the total effective aspects in system optimum size, the thermo-economic-environmental criteria is defined. By the help of databank of parametric analysis, the optimum design variables are determined by employing the GA optimization algorithm. In the following, an intelligence neural network is developed to learn the reliable correlation between the inputs and outputs data. Finally, the optimum size of each subsystem is determined by using triple-objective MPSO. Based on detailed economic analysis, the system payback period is estimated about 450 days which is 41% less than the conventional system. The daily COP and exergy efficiency of the whole system has improved up to 98% and 40%, after substituting the optimum design variable parameters. Triple-objective MPSO results show that, the ice storage tank should be selected 22% smaller than the initial amount. |
| format | Article |
| id | doaj-art-1fe5a315531d4f568e805b4f40f29dc7 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-1fe5a315531d4f568e805b4f40f29dc72025-08-20T02:33:05ZengNature PortfolioScientific Reports2045-23222024-11-0114112510.1038/s41598-024-78994-zThe optimum sizing of zero-emission water-cooled VCR cycle based on exergo-economic-environmental assessment criteria by triple-objective MPSOSeyedeh Mohadeseh Miri0Mahmood Farzaneh-Gord1Alireza Hosseinpour2Mohit Bajaj3Ievgen Zaitsev4Department of Mechanical Engineering, Faculty of Engineering, University of ZabolMechanical Engineering Department, Faculty of Engineering, Ferdowsi University of MashhadDepartment of Electrical Engineering, Faculty of Engineering, University of ZabolDepartment of Electrical Engineering, Graphic Era (Deemed to Be University)Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of UkraineAbstract Renewable energies are interesting as an alternative and sustainable resource for air conditioning applications. But initial investment cost of equipment, whose employed for converting the renewable energy into usable shape and also for air conditioning duty, are significant. Therefore, determining the optimum sizing has high priority. In current study, water cooled vapor compression refrigeration cycle powered by wind energy and storage tank is proposed, simulated and optimized. To contribute the total effective aspects in system optimum size, the thermo-economic-environmental criteria is defined. By the help of databank of parametric analysis, the optimum design variables are determined by employing the GA optimization algorithm. In the following, an intelligence neural network is developed to learn the reliable correlation between the inputs and outputs data. Finally, the optimum size of each subsystem is determined by using triple-objective MPSO. Based on detailed economic analysis, the system payback period is estimated about 450 days which is 41% less than the conventional system. The daily COP and exergy efficiency of the whole system has improved up to 98% and 40%, after substituting the optimum design variable parameters. Triple-objective MPSO results show that, the ice storage tank should be selected 22% smaller than the initial amount.https://doi.org/10.1038/s41598-024-78994-zCompression cycle5E analysisWind energyTriple-objective MPSO optimizationCold storage |
| spellingShingle | Seyedeh Mohadeseh Miri Mahmood Farzaneh-Gord Alireza Hosseinpour Mohit Bajaj Ievgen Zaitsev The optimum sizing of zero-emission water-cooled VCR cycle based on exergo-economic-environmental assessment criteria by triple-objective MPSO Scientific Reports Compression cycle 5E analysis Wind energy Triple-objective MPSO optimization Cold storage |
| title | The optimum sizing of zero-emission water-cooled VCR cycle based on exergo-economic-environmental assessment criteria by triple-objective MPSO |
| title_full | The optimum sizing of zero-emission water-cooled VCR cycle based on exergo-economic-environmental assessment criteria by triple-objective MPSO |
| title_fullStr | The optimum sizing of zero-emission water-cooled VCR cycle based on exergo-economic-environmental assessment criteria by triple-objective MPSO |
| title_full_unstemmed | The optimum sizing of zero-emission water-cooled VCR cycle based on exergo-economic-environmental assessment criteria by triple-objective MPSO |
| title_short | The optimum sizing of zero-emission water-cooled VCR cycle based on exergo-economic-environmental assessment criteria by triple-objective MPSO |
| title_sort | optimum sizing of zero emission water cooled vcr cycle based on exergo economic environmental assessment criteria by triple objective mpso |
| topic | Compression cycle 5E analysis Wind energy Triple-objective MPSO optimization Cold storage |
| url | https://doi.org/10.1038/s41598-024-78994-z |
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