Fuzzy Logic Modeling of Energy and Exergy Efficiencies in Drying Units Powered by Renewable Energy Sources
Abstract
Today, exergy analyses have become essential for addressing critical engineering and environmental issues, such as improving energy efficiency, sustainable resource utilization, and reducing environmental impacts. To enhance the potential of these studies in generating more effective and precise results, new methods, like fuzzy logic, have been successfully employed in the analysis and decision-making processes. This article examines the energy and exergy analyses and integrating these analyses with fuzzy logic. The Organic Rankine Cycle systems, denoted as ORC-1 and ORC-2, exhibit energy efficiencies of 10.66% and 10.92%, respectively, with ORC-2 displaying an exergy efficiency increase to 86.8%. The cooling system boasts a Coefficient of Performance (COP) of 3.64 and an exergy efficiency of 25.3%. With fuzzy logic method, the estimated exergy efficiency for ORC-1 reached 99.38%, and the energy efficiency was estimated at 97.33%. For ORC-2, the exergy efficiency was estimated at 98.66%, and the energy efficiency was estimated at 99.42%. The refrigerant quantity for the cooling system was estimated at 97.7%, and the COP was estimated at 98.03%.
References
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Yenilenebilir Enerji Kaynakları ile Beslenen Kurutma Ünitelerinde Enerji ve Ekserji Verimlerinin Bulanık Mantık Modellemesi
Abstract
Günümüzde ekserji analizleri, enerji verimliliği artırma, kaynakların sürdürülebilir kullanımı ve çevresel etkilerin azaltılması gibi kritik mühendislik ve çevre sorunlarını ele almak için vazgeçilmez hale gelmiştir. Bu çalışmaların daha etkili ve kesin sonuçlar üretme potansiyelini artırmak amacıyla, bulanık mantık gibi yeni yöntemler, analiz ve karar verme süreçlerine başarıyla uygulanmaktadır. Bu makalede, enerji ve ekserji analizleri ve bulanık mantık modellemesi incelenmiştir. ORC-1 ve ORC-2 olarak adlandırılan Organik Rankine Çevrimi sistemleri sırasıyla enerji verimliliği %10.66 ve %10.92'ye sahiptir, ancak ORC-2'nin ekserji verimi %86.8'e yükselir. Soğutma sistemi ise 3.64'lük bir COP değeri ve %25.3'lük ekserji verimine sahiptir. Bulanık mantık metodu ile: ORC-1 için ekserji verimliliği %99,38, enerji verimliliği ise %97,33 olarak tahmin edilmiştir. ORC-2 için ekserji verimliliği %98,66, enerji verimliliği ise %99,42 olarak tahmin edilmiştir. Soğutma sistemi için soğutkan miktarı %97,7, COP ise %98,03 olarak tahmin edilmiştir.
References
- 1. Situmorang, Z., Husein, A.E., 2023. Comparison of Intelligent Fuzzy Controller and Fuzzy Rule Suram Algorithms in the Drying Process. Information Sciences Letters, 12(6), 2603-2621.
- 2. Hosseinpour, S., Martynenko, A., 2022. Application of Fuzzy Logic in Drying: A review. Drying Technology, 40(5), 797-826.
- 3. Rahman, S.A., Nassef, A.M., Rezk, H., Assad, M.E.H., Hoque, M.E., 2021. Experimental Investigations and Modeling of Vacuum Oven Process Using Several Semi-Empirical Models and a Fuzzy Model of Cocoa Beans. Heat and Mass Transfer, 57, 175-188.
- 4. Jahedi Rad, S., Kaveh, M., Sharabiani, V.R., Taghinezhad, E., 2018. Fuzzy Logic, Artificial Neural Network and Mathematical Model for Prediction of White Mulberry Drying Kinetics. Heat and Mass Transfer, 54, 3361-3374.
- 5. Zoukit, A., El Ferouali, H., Salhi, I., Doubabi, S., Abdenouri, N., 2019. Takagi Sugeno Fuzzy Modeling Applied to an Indirect Solar Dryer Operated in Both Natural and Forced Convection. Renewable Energy, 133, 849-860.
- 6. Gao, T., Liu, C., 2017. Off-Design Performances of Subcritical and Supercritical Organic Rankine Cycles in Geothermal Power Systems Under an Optimal Control Strategy. Energies, 10(8), 1185.
- 7. Yaïci, W., Annuk, A., Entchev, E., Longo, M., Kalder, J., 2021. Organic Rankine Cycle-Ground Source Heat Pump with Seasonal Energy Storage Based Micro-Cogeneration System in Cold Climates: The Case for Canada. Energies, 14(18), 5705.
- 8. Khan, B., Kim, M.H., 2022. Energy and Exergy Analyses of a Novel Combined Heat and Power System Operated by a Recuperative Organic Rankine Cycle Integrated with a Water Heating System. Energies, 15(18), 6658.
- 9. Akarslan Kodaloğlu, F., Elbir, A., Sahin, M.E., 2023. Wool Drying Process In Heat-Pump-Assisted Dryer by Fuzzy Logic Modelling. Thermal Science, 27(4 Part B), 3043-3050.
- 10. Kumaresan, G., 2013. Optimizing Design of Heat Pump Using Fuzzy Logic and Genetic Algorithm. International Journal of Engineering Research and Applications (IJERA), 3, 1184-1189.
- 11. Dincer, I, Rosen, M.A., 2012. Exergy: Energy, Environment and Sustainable Development. Elsevier Science, 551.
- 12. Cengel, Y.A., Boles, M.A., Kanoğlu, M., 2011. Thermodynamics: an Engineering Approach. New York: McGraw-Hill, 445.
- 13. Wang L.X., 1997. A Course in Fuzzy Systems and Control. New Jersey: Prentice Hall, 424.
- 14. Czabanski, R., Jezewski, M., Leski, J., 2017. Introduction to Fuzzy Systems. Theory and Applications of Ordered Fuzzy Numbers. 356, 23-43.
- 15. Elmas, Ç., 2003. Bulanık Mantık Denetleyiciler. Seçkin Yayıncılık, Ankara, 230.
- 16. Arslan, A., Kaya. M., 2001. Determination of Fuzzy Logic Membership Functions Using Genetic Algorithms. Fuzzy Sets and Systems, 118(2), 297-306,
- 17. Bağış, A., 2003. Determining Fuzzy Membership Functions With Tabu Search an Application to Control. Fuzzy Sets and Systems, 139(1), 209-225.
- 18. Jiang, H., Deng, H., He, Y., 2008. Determination of Fuzzy Logic Membership Function Using Extended Ant Colony Optimization Algorithm. Fifth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). Shandong, China, 1, 581-585,
- 19. Acilar A.M., Arslan, A., 2011. Optimization of Multiple Input-Output Fuzzy Membership Functions Using Clonal Selection Algorithm. Expert Systems with Applications, 38(3), 1374-1381.
- 20. Ross, T.J., 2004. Fuzzy Logic with Engineering Applications. John Wiley Sons Ltd, Chichester, 628.
- 21. Sivanandam, S.N., Sumathi, S., Deepa, S.N., 2007. Introduction to Fuzzy Logic Using MATLAB. Springer, Berlin, 430.
- 22. Şen, Z., 2020. Bulanık Mantık İlkeleri ve Modelleme. Su Vakfı, 368.
- 23. Klein, S.A., 2020. Engineering Equation Solver (EES) F-Chart Software, Version 10.835-3D.
Details
| Primary Language | English |
|---|---|
| Subjects | Energy, Renewable Energy Resources |
| Journal Section | Articles |
| Authors | |
| Publication Date | December 28, 2023 |
| Submission Date | November 1, 2023 |
| Acceptance Date | December 25, 2023 |
| Published in Issue | Year 2023 Volume: 38 Issue: 4 |
