Thermodynamic Analysis and Multi-Objective Optimization of Solar Heat Engines
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RESEARCH ARTICLE-MECHANICAL ENGINEERING
Thermodynamic Analysis and Multi-Objective Optimization of Solar Heat Engines Yasin Ust1 · Ibrahim Ozsari1
· Feyyaz Arslan1,2 · Aykut Safa1
Received: 10 April 2020 / Accepted: 13 August 2020 © King Fahd University of Petroleum & Minerals 2020
Abstract 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. Keywords Heat engine performance · Overall efficiency · Power output · Solar-driven heat engine · Thermo-economic optimization
List of Symbols a A ANN b c C d C˙ I F
B
Investment cost parameter (NCU/year W) Heat transfer area (m2 ) Artificial neural networks Operating and maintenance cost parameter (NCU/year W) Total cost parameter (NCU/year W) Cost (NCU/year) Lost exergy cost parameter (NCU/year W) Internal conductance Objective function
Ibrahim Ozsari [email protected]
1
Department of Naval Architecture and Marine Engineering, Yildiz Technical University, Besiktas 34349, Istanbul, Turkey
2
Barbaros Hayrettin Naval Architecture and Maritime Faculty, Iskenderun Technical University, Iskenderun 31200, Hatay, Turkey
f HE NCU R SD-HE SD-ExCR T TEOF U Q˙ W˙ X
Economical parameter c/(c + d) Heat engine National currency unit Internal irreversibility parameter Solar-driven heat engine Solar-driven external combustion regenerative Temperature (K) Thermo-economic objective function Overall heat transfer coefficient (W/m2 K for convection or W/m2 K4 for radiation) Rate of heat transfer (W) Power output (W) X TTcoll
Y
TY Tamb
Greek Symbols β
UHR 3 UHC TH
123
Arabian Journal
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