Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/88499
Title: Multiobjective Thermoeconomic Optimization of the LNG Cold Utilized Micro-cogeneration System
Authors: Kanbur, Baris Burak
Dubey, Swapnil
Fei, Duan
Choo, Fook Hoong
Xiang, Liming
Keywords: Multiobjective Optimization
Genetic Algorithm
Issue Date: 2018
Conference: 2018 2nd International Conference on Green Energy and Applications
Abstract: Liquefied natural gas (LNG) cold utilization systems are feasible options for the inland and stranded regions where the conventional pipeline technology is challenging. For the best operation conditions of the systems in the real engineering applications, the optimization is a significant step after the design and analysis steps. This study aims to optimize an LNG cold utilized micro-cogeneration system by using the multiobjective optimization strategy with the genetic algorithm. Thermodynamic and thermoeconomic investigations are performed, and then the multiobjective optimization study is carried out according to the net generated power rate, exergetic efficiency, and the levelized product cost as multiobjectives. The study is conducted between 288.15 K and 313.15 K, and the optimum operation conditions are detected between 301.0 K and 302.5 K with respect to the different relative humidities.
URI: https://hdl.handle.net/10356/88499
http://hdl.handle.net/10220/44896
DOI: 10.1109/ICGEA.2018.8356288
Schools: Interdisciplinary Graduate School (IGS) 
School of Mechanical and Aerospace Engineering 
School of Physical and Mathematical Sciences 
Research Centres: Energy Research Institute @ NTU (ERI@N) 
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/ICGEA.2018.8356288].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:IGS Conference Papers

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