An Optimized Heat Sink for Thermophotovoltaic Panels

Document Type: Research Paper


1 D.I.N.,University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy

2 CIRI Aeronautica, University of Bologna, Via Fontanelle 40, 47121 Forli, Italy


In the present work, an innovative hybrid solar panel is proposed, which can be used to pave floors or to cover roofs. A particular heat sink is employed, which gives robustness to the panel and provides a better heat transfer effectiveness with respect to tube heat exchangers. The geometry of the heat sink which is employed in the panel is optimized with the help of a numerical model and a genetic algorithm. Some optimization examples are shown. The velocity and temperature distributions on the heat sink cross section are also investigated. The presented hybrid panel allows till 20% increase in the electrical efficiency with respect to a simple photovoltaic panel. Moreover, it can be easily installed under every environmental condition due to its robustness and resistance to water infiltration. 


Main Subjects

[1]     Dupré, O., Vaillon, R., & Green, M. A. (2015). Physics of the temperature coefficients of solar cells. Solar energy materials and solar cells140, 92-100.

[2]     Polman, A., & Atwater, H. A. (2012). Photonic design principles for ultrahigh-efficiency photovoltaics. Nature materials11(3), 174.

[3]      Michael, J. J., Iniyan, S., & Goic, R. (2015). Flat plate solar photovoltaic–thermal (PV/T) systems: a reference guide. Renewable and sustainable energy reviews51, 62-88.

[4]     Santbergen, R., & van Zolingen, R. C. (2008). The absorption factor of crystalline silicon PV cells: A numerical and experimental study. Solar energy materials and solar cells92(4), 432-444.

[5]     Santbergen, R. (2008). Optical absorption factor of solar cells for PVT systems (Doctoral dissertation, Eindhoven University of Technology). Retrieved from

[6]     Tripanagnostopoulos, Y., Nousia, T. H., Souliotis, M., & Yianoulis, P. (2002). Hybrid photovoltaic/thermal solar systems. Solar energy72(3), 217-234.

[7]     Charalambous, P. G., Kalogirou, S. A., Maidment, G. G., & Yiakoumetti, K. (2011). Optimization of the photovoltaic thermal (PV/T) collector absorber. Solar energy85(5), 871-880.

[8]     Garg, H. P., & Agarwal, R. K. (1995). Some aspects of a PV/T collector/forced circulation flat plate solar water heater with solar cells. Energy conversion and management36(2), 87-99.

[9]     Zondag, H. A., De Vries, D. W., Van Helden, W. G. J., Van Zolingen, R. J. C., & Van Steenhoven, A. A. (2003). The yield of different combined PV-thermal collector designs. Solar energy74(3), 253-269.

[10] Zondag, H. A., de Vries, D. D., Van Helden, W. G. J., Van Zolingen, R. J. C., & Van Steenhoven, A. A. (2002). The thermal and electrical yield of a PV-thermal collector. Solar energy72(2), 113-128.

[11] Tiwari, A., & Sodha, M. S. (2006). Performance evaluation of hybrid PV/thermal water/air heating system: a parametric study. Renewable energy31(15), 2460-2474.

[12] Grefenstette, J. J. (1986). Optimization of control parameters for genetic algorithms. IEEE transactions on systems, man, and cybernetics16(1), 122-128.

[13] Deb, K. (2014). Multi-objective optimization. Search methodologies (pp. 403-449). Springer, Boston, MA.

[14] Deb, K., Anand, A., & Joshi, D. (2002). A computationally efficient evolutionary algorithm for real-parameter optimization. Evolutionary computation10(4), 371-395.

[15] Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. A. M. T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE transactions on evolutionary computation6(2), 182-197.

[16] Farina, M., Deb, K., & Amato, P. (2004). Dynamic multiobjective optimization problems: test cases, approximations, and applications. IEEE transactions on evolutionary computation8(5), 425-442.

[17] Peigin, S., Epstein, B., & Gali, S. (2004). Multilevel parallelization strategy for optimization of aerodynamic shapes. Parallel computational fluid dynamics 2003, 505-512.

[18] Queipo, N., Devarakonda, R., & Humphrey, J. A. C. (1994). Genetic algorithms for thermosciences research: application to the optimized cooling of electronic components. International journal of heat and mass transfer37(6), 893-908.

[19] Peng, H., & Ling, X. (2008). Optimal design approach for the plate-fin heat exchangers using neural networks cooperated with genetic algorithms. Applied thermal engineering28(5-6), 642-650.

[20] Chow, T. T., Zhang, G. Q., Lin, Z., & Song, C. L. (2002). Global optimization of absorption chiller system by genetic algorithm and neural network. Energy and buildings34(1), 103-109.

[21] Gosselin, L., Tye-Gingras, M., & Mathieu-Potvin, F. (2009). Review of utilization of genetic algorithms in heat transfer problems. International journal of heat and mass transfer52(9-10), 2169-2188.

[22] Azarkish, H., Sarvari, S. M. H., & Behzadmehr, A. (2010). Optimum design of a longitudinal fin array with convection and radiation heat transfer using a genetic algorithm. International journal of thermal sciences49(11), 2222-2229.

[23] Sanaye, S., & Hajabdollahi, H. (2010). Thermal-economic multi-objective optimization of plate fin heat exchanger using genetic algorithm. Applied energy87(6), 1893-1902.

[24] Najafi, H., Najafi, B., & Hoseinpoori, P. (2011). Energy and cost optimization of a plate and fin heat exchanger using genetic algorithm. Applied thermal engineering31(10), 1839-1847.

[25] Das, R. (2012). Application of genetic algorithm for unknown parameter estimations in cylindrical fin. Applied soft computing12(11), 3369-3378.

[26] Amini, M., & Bazargan, M. (2014). Two objective optimization in shell-and-tube heat exchangers using genetic algorithm. Applied thermal engineering69(1-2), 278-285.

[27] Patel, V. K., & Savsani, V. J. (2015). Heat transfer search (HTS): a novel optimization algorithm. Information sciences324, 217-246.

[28] Wen, J., Yang, H., Tong, X., Li, K., Wang, S., & Li, Y. (2016). Configuration parameters design and optimization for plate-fin heat exchangers with serrated fin by multi-objective genetic algorithm. Energy conversion and management117, 482-489.

[29] Biyanto, T. R., Gonawan, E. K., Nugroho,nG., Hantoro, R., Cordova, H., & Indrawati, K. (2016). Heat exchanger network retrofit throughout overall heat transfer coefficient by using genetic algorithm. Applied thermal engineering, 94, 274-281.

[30] Khan, T. A., & Li, W. (2017). Optimal design of plate-fin heat exchanger by combining multi-objective algorithms. International journal of heat and mass transfer108, 1560-1572.

[31] Fabbri, G. (1997). A genetic algorithm for fin profile optimization. International journal of heat and mass transfer40(9), 2165-2172.

[32] Fabbri, G. (1998). Optimization of heat transfer through finned dissipators cooled by laminar flow. International journal of heat and fluid flow19(6), 644-654.

[33] Fabbri, G., Greppi, M., & Lorenzini, M. (2012). Optimization with genetic algorithms of PVT system global efficiency. Journal of energy and power engineering6(7), 1035.