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Application of Gene Expression Programming for Performance Analysis of a Regenerative Organic Rankine Cycle with Low-Temperature Heat Source

Arzu Şencan Şahin*, Erkan Dikmen

Mechanical Engineering Department, Technology Faculty, Isparta University of Applied Sciences, Isparta, Turkey.

*Corresponding author: Arzu Şencan Şahin

Date: January 25,2022 Hits: 882


In this study, the performance analysis of the Regenerative Organic Rankine Cycle (RORC) by using the Gene Expression Programming (GEP) was carried out. Working fluids R-123 and R-134a have been used in the RORC. GEP model was developed to predict thermodynamic performances of the RORC depending on the steam generator, condenser, subcooling, and superheating temperature. To investigate the accuracy of the model, root mean square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2) was employed. For R123, the optimal values of RMSE, MAPE, and R2 are 0.00004228, 0.01377, and 0.9532, respectively. For R-134a, the optimal values of RMSE, MAPE, and R2 are 0.00002413, 0.01226, and 0.9613, respectively. The results showed that the GEP model results and actual values are in fairly well agreement. The formulas obtained from the GEP model are relatively short, simple and reliable. So, these formulas will assist engineers to very accurately and quickly estimate the thermal efficiency of the regenerative organic Rankine cycle.


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Application of Gene Expression Programming for Performance Analysis of a Regenerative Organic Rankine Cycle with Low-Temperature Heat Source

How to cite this paper: Arzu Şencan Şahin, Erkan Dikmen. (2022) Application of Gene Expression Programming for Performance Analysis of a Regenerative Organic Rankine Cycle with Low-Temperature Heat Source. Journal of Electrical Power & Energy Systems6(1), 24-33.

DOI: http://dx.doi.org/10.26855/jepes.2022.01.003