OPEN ACCESS
Stirling engines are close cycle motors which can output mechanical work following a difference in temperature of two whatever thermal sources. This paper presents the preliminary design and the optimization of a system composed by a Low Differential Temperature Stirling Engine moving a simple single effect reciprocating water pump. The heat source is solar radiation, so that the engine can be installed in developing countries or in remote installation, without the need for fossil fuels. According to literature, the design of a Stirling engine is a complex task, since a lot of parameters should be considered at the same time; a mathematical model of the whole system, based on the second order theory for Stirling engine, has been implemented. In the following, it has been exploited to perform the optimization of the engine/pump mechanical system: maximum water flow for given maximum engine dimensions is the design goal of this problem. The Genetic Algorithms, Particle Swarm, Monte Carlo, Differential Evolution, Imperialist Comptetitive, and Simulated Annealing heuristic algorithms have been applied to solve the problem and to compare each other. The results obtained confirm the usefulness of the optimization in supporting the designer in such a complex task, in which a very accurate design is necessary to increase the efficiency of the system.
[1] Senft, J.R. (1993) Ringbom Stirling Engines. Oxford University Press New York
[2] Kongtragool, B., Wongwises, S. A review of solar-powered Stirling engines and low temperature differential Stirling engines (2003) Renewable and Sustainable Energy Reviews, 7 (2), pp. 131-154. doi: 10.1016/S1364-0321(02)00053-9
[3] Sharma, A., Shukla, S.K., Rai, A.K. Finite time thermodynamic analysis and optimization of solar-dish Stirling heat engine with regenerative losses (2011) Thermal Science, 15 (4), pp. 995-1009. http://thermalscience.vinca.rs.ezproxy3.lhl.uab.edu/pdfs/papers-2011/TSCI1104181015S.pdf doi: 10.2298/TSCI110418101S
[4] Asnaghi, A., Ladjevardi, S.M., Saleh Izadkhast, P., Kashani, A.H. Thermodynamics performance analysis of solar Stirling engines (2012) ISRN Renewable Energy, p. 14. 2012, Article ID 321923
[5] Tavakolpour, A.R., Zomorodian, A., Akbar Golneshan, A. Simulation, construction and testing of a two-cylinder solar Stirling engine powered by a flat-plate solar collector without regenerator (2008) Renewable Energy, 33 (1), pp. 77-87. doi: 10.1016/j.renene.2007.03.004
[6] Kongtragool, B., Wongwises, S. Performance of low-temperature differential Stirling engines (2007) Renewable Energy, 32 (4), pp. 547-566. doi: 10.1016/j.renene.2006.03.003
[7] Kwanchai, K., Mahkamov, K. Thermodynamic and CFD modelling of low temperature difference stirling engines (2009) Proceedings of the 14th International Stirling Engine Conference. Groningen, The Netherlands
[8] Urieli, I., Berchowitz, D. Stirling cycle engine analysis (1984) Adam Hilger Ltd.
Bristol
[9] Timoumi, Y., Tlili, I., Ben Nasrallah, S. Performance optimization of Stirling engines (2008) Renewable Energy, 33 (9), pp. 2134-2144. doi: 10.1016/j.renene.2007.12.012
[10] Kwanchai, K., Mahkamov, K.Optimization of low temperature difference solar stirling engines using genetic algorithm (2011) Proceeding of World Renewable Energy Congress Linkoping, Sweeden
[11] Kagawa, N. An experimental study of A 3-kW Stirling engine (2000) 35th Intersociety Energy Conversion Engineering Conference and Exhibit, pp. 92-100.
[12] Sikora, M., Vlach, R. Dynamic model of stirling engine crank mechanism with connected electric generator Applied and Computational Mechanics, 3 (1), pp. 185-194.
[13] Chen, N.C.J., Griffin, F.P. A review of stirling engine mathematical models (1983) Oak Ridge National Laboratory, ORNL/CON-135. August
[14] Timoumi, Y., Tlili, I., Ben Nasrallah, S. Design and performance optimization of GPU-3 Stirling engines (2008) Energy, 33 (7), pp. 1100-1114. www.elsevier.com/inca/publications/store/4/8/3/ doi: 10.1016/j.energy.2008.02.005
[15] Tlili, I., Timoumi, Y., Nasrallah, S.B. Analysis and design consideration of mean temperature differential Stirling engine for solar application (2008) Renewable Energy, 33 (8), pp. 1911-1921. doi: 10.1016/j.renene.2007.09.024
[16] Martini, W.R. Stirling engine design manual (1983) Richland: Martini Engineering.
[17] Tanaka, Makoto, Yamashita, Iwao, Chisaka, Fumitake Flow and heat transfer characteristics of the stirling engine regenerator in an oscillating flow (1990) JSME International Journal, Series 2: Fluids Engineering, Heat Transfer, Power, Combustion, Thermophysical Properties, 33 (2), pp. 283-289. doi: 10.1299/jsmeb1988.33.2_283
[18] Rishel, J. Water pumps and pumping systems (2002) McGraw Hill ISBN-13: 978-0071374910
[19] Karassik, I.J. Pump handbook (2001) Harvard Business Review Books - McGraw-Hill
ISBN: 9780070340329
[20] Ceruti, A., Caligiana, G., Persiani, F. Comparative evaluation of different optimization methodologies for the design of UAVs having shape obtained by hot wire cutting techniques (2013) International Journal on Interactive Design and Manufacturing, 7 (2), pp. 63-78. doi: 10.1007/s12008-012-0164-x
[21] Ceruti, A., Voloshin, V., Marzocca, P. Multi-disciplinary design optimization of unconventional airship configuration with heuristic algorithms (2013) 54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. http://arc.aiaa.org/doi/pdf/10.2514/6.2013-1676 ISBN: 978-162410223-3 doi: 10.2514/6.2013-1676
[22] Tornabene, F., Ceruti, A. Mixed static and dynamic optimization of four-parameter functionally graded completely doubly curved and degenerate shells and panels using GDQ method (2013) Mathematical Problems in Engineering, 2013, art. no. 867079. doi: 10.1155/2013/867079
[23] Goldberg, D.E. Genetic algorithms in search, optimization and machine learning
(1989) Addison-Wesley Pub. Co. Reading, MA
[24] Fishman, G.S. Monte carlo: Concepts, algorithms, and applications (1995) Springer, New York. ISBN 0-387-94527-X
[25] Kennedy, James, Eberhart, Russell Particle swarm optimization (1995) IEEE International Conference on Neural Networks - Conference Proceedings, 4, pp. 1942-1948.
[26] Storn, R., Price, K. Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces (1997) Journal of Global Optimization, 11 (4), pp. 341-359. www.kluweronline.com/issn/0925-5001/ doi: 10.1023/A:1008202821328
[27] Hoos, H.H., Stützle, T. Stochastic local search: Foundations and applications
(2005) Elsevier.Amsterdam
[28] Atashpaz-Gargari, E., Lucas, C. Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition (2007) 2007 IEEE Congress on Evolutionary Computation, CEC 2007, art. no. 4425083, pp. 4661-4667. ISBN: 1424413400; 978-142441340-9 doi: 10.1109/CEC.2007.4425083
[29] Piancastelli, L., Frizziero, L., Rocchi, I. An innovative method to speed up the finite element analysis of critical engine components (2012) International Journal of Heat and Technology, 30 (2), pp. 127-132. http://www.iieta.org/Journals/IJHT/Archive doi: 10.18280/ijht.300218