Analysis and multi-objective optimization of SOFC/GT/SCO2 hybrid power system based on thermodynamics and economics
•A new hybrid power system based on solid oxide fuel cell is proposed.•Different arrangements of supercritical CO2 cycles affect system performance.•Evaluating the system from a thermodynamic and economic perspective.•Effects of some significant parameters on system performance is analyzed.•The mult...
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| Vydané v: | Applied thermal engineering Ročník 232; s. 121033 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier Ltd
01.09.2023
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| ISSN: | 1359-4311 |
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| Abstract | •A new hybrid power system based on solid oxide fuel cell is proposed.•Different arrangements of supercritical CO2 cycles affect system performance.•Evaluating the system from a thermodynamic and economic perspective.•Effects of some significant parameters on system performance is analyzed.•The multi-objective genetic algorithm is used to find the optimal design point.
SOFC/GT hybrid power systems with the advantages of high energy efficiency and low emissions are important directions of energy research. This study proposes a new SOFC/GT/SCO2 hybrid power system, in which the SCO2 cycle is placed inside the SOFC/GT subsystem, and the waste heat of the SCO2 cycle is used for heating the air of the system to achieve good thermal matching between the system. After system construction, the system is thermodynamically and economically evaluated, and the influence of parameters on system operation performance is investigated. The system’s energy efficiency and the electricity production cost are optimized by a multi-objective genetic algorithm. The optimized net output power, energy efficiency, and exergy efficiency of the system are increased to 226.374 kW, 60.42%, and 63.03%, respectively, and the electricity production cost decreases to 0.079 $/kWh. Results show that placing the SCO2 cycle inside the SOFC/GT subsystem instead of at the tail can improve the energy efficiency of the system and effectively realize gradient energy utilization in the SOFC/GT/SCO2 hybrid power system. |
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| AbstractList | •A new hybrid power system based on solid oxide fuel cell is proposed.•Different arrangements of supercritical CO2 cycles affect system performance.•Evaluating the system from a thermodynamic and economic perspective.•Effects of some significant parameters on system performance is analyzed.•The multi-objective genetic algorithm is used to find the optimal design point.
SOFC/GT hybrid power systems with the advantages of high energy efficiency and low emissions are important directions of energy research. This study proposes a new SOFC/GT/SCO2 hybrid power system, in which the SCO2 cycle is placed inside the SOFC/GT subsystem, and the waste heat of the SCO2 cycle is used for heating the air of the system to achieve good thermal matching between the system. After system construction, the system is thermodynamically and economically evaluated, and the influence of parameters on system operation performance is investigated. The system’s energy efficiency and the electricity production cost are optimized by a multi-objective genetic algorithm. The optimized net output power, energy efficiency, and exergy efficiency of the system are increased to 226.374 kW, 60.42%, and 63.03%, respectively, and the electricity production cost decreases to 0.079 $/kWh. Results show that placing the SCO2 cycle inside the SOFC/GT subsystem instead of at the tail can improve the energy efficiency of the system and effectively realize gradient energy utilization in the SOFC/GT/SCO2 hybrid power system. |
| ArticleNumber | 121033 |
| Author | Ying, Chao Yao, Shouguang Xia, Minjie |
| Author_xml | – sequence: 1 givenname: Minjie orcidid: 0009-0001-3175-9955 surname: Xia fullname: Xia, Minjie – sequence: 2 givenname: Shouguang orcidid: 0000-0003-0207-9309 surname: Yao fullname: Yao, Shouguang email: zjyaosg@126.com – sequence: 3 givenname: Chao orcidid: 0009-0002-0302-1803 surname: Ying fullname: Ying, Chao |
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| Keywords | SOFC/GT/SCO2 Multi-objective genetic algorithm Electricity production cost Energy efficiency Exergy efficiency |
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