Sustainability and thermoenvironmental indicators on the multiobjective optimization of the liquefied natural gas fired micro-cogeneration systems
Liquefied natural gas (LNG), a clean fuel type mainly containing methane, has been becoming more popular amongst the other fuels for the power generation systems. Although there are a lot of thermodynamic and thermoeconomic assessments about the LNG fired power generation systems, the environmental...
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Main Authors: | , , , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2021
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/150648 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | Liquefied natural gas (LNG), a clean fuel type mainly containing methane, has been becoming more popular amongst the other fuels for the power generation systems. Although there are a lot of thermodynamic and thermoeconomic assessments about the LNG fired power generation systems, the environmental and sustainability aspects have still lack investigation, especially on the optimization step. To minimize this gap, a multiobjective optimization study is performed for the LNG fired micro-cogeneration system. The current study considers various objective functions from thermodynamic, environmental, thermoeconomic, and sustainability aspects. A newly developed sustainability index is used as one of the objective functions in the study. The approach is defined as the complex multiobjective optimization procedure that constitutes different multiobjective optimization groups to better understand and evaluate the different objective functions together. The controllable air temperature and relative humidity are selected as the external decision variables. The best trade-off regions are identified between 300.00 K and 313.15 K at the relative humidity of 90% while they are found between 310.15 K and 313.15 K at the relative humidity of 50%. The high relative humidity and ambient air temperature present the best climatic conditions for the optimal operation of the small-scale system during the indoor operations. |
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