Thermodynamic Analysis and Multi-Objective Optimization of Solar Heat Engines

被引:4
|
作者
Ust, Yasin [1 ]
Ozsari, Ibrahim [1 ]
Arslan, Feyyaz [1 ,2 ]
Safa, Aykut [1 ]
机构
[1] Yildiz Tech Univ, Dept Naval Architecture & Marine Engn, TR-34349 Istanbul, Turkey
[2] Iskenderun Tech Univ, Barbaros Hayrettin Naval Architecture & Maritime, TR-31200 Iskenderun, Hatay, Turkey
关键词
Heat engine performance; Overall efficiency; Power output; Solar-driven heat engine; Thermo-economic optimization; OPTIMUM PERFORMANCE-CHARACTERISTICS; ENTROPY GENERATION MINIMIZATION; ORGANIC RANKINE-CYCLE; MAXIMUM POWER; THERMOECONOMIC OPTIMIZATION; STIRLING ENGINE; WASTE HEAT; DRIVEN; SYSTEM; EFFICIENCY;
D O I
10.1007/s13369-020-04880-1
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Detailed performance analysis for a thermal system using a generalized irreversible solar-driven heat engine model is performed. The heat engine (HE) model is formed by the first and the second laws of thermodynamics and economical considerations. Also, the HE is optimized under the thermo-economic objective function (TEOF), power output, and overall efficiency criteria. The TEOF is used to evaluate the investment, including lost exergy, and operating and maintenance costs together. It is defined as the power output per unit total cost. In the HE model, investment and operating and maintenance costs are regarded as proportional to the power output of the heat engine, while lost exergy cost is regarded as proportional to the entropy generation rate. In thermal system designs, various scenarios are considered regarding size and configuration limits. To fulfill the requirements, performance output parameters can be evaluated with weighing factors. In the HE model, the hot surface heat transfer mechanisms are considered as both radiation and convection, but the cold surface heat transfer mechanism is considered as convection, only. Also, the thermo-economic performance is evaluated considering heat losses. Besides overall efficiency and operational temperatures of the hot working fluid have been discoursed in detail. HE model performance data and optimized results are computed numerically. And finally, an artificial neural network model is presented for an alternative solution to compute HE performance data with less effort and less input data.
引用
收藏
页码:9669 / 9684
页数:16
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