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Thermo-economic-environmental optimization of a 100 kW microturbine has been numerically investigated by genetic algorithm optimization method. An objective function is defined as the sum of the total cost of the plant and the costs of environmental pollutant effects (the emission of NOx and CO gases due to fuel combustion), while the design parameters are the common important parameters of an industrial power plant cycle. The objective function is then formulated in the design parameters. Finally, the optimum values of the parameters are computed by minimizing the objective function using the Genetic Algorithm (GA).
PAPER REVISED: 2013-12-11
PAPER ACCEPTED: 2013-12-14
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THERMAL SCIENCE YEAR 2015, VOLUME 19, ISSUE Issue 2, PAGES [475 - 487]
  1. Hamilton, S.L., The Handbook of Microturbine Generators, PennWell Corporation, Tulsa, USA, 2003
  2. Opdyke, D.E., Franus, D.J., Gas Turbine Industry Set to Rebound, Turbomachinery International Handbook, 44 (2004), 6, Business Journals Inc., CT, USA
  3. Technology characterization-microturbine, Energy Nexus Group, Environmental Protection Agency, USA, 2002
  4. Sun, Z., Xie, N., Experimental Studying of a Small Combined Cold and Power Systems Driven by a Micro Gas Turbine, Applied Thermal Engineering, 30 (2010), 10, pp. 1242-1246
  5. Sanaye, S., et. al., Selecting the Prime Movers and Nominal Powers in Combined Heat and Power Systems, Applied Thermal Engineering, 28 (2008), 10, pp. 1177-1188
  6. Hinnells, M., Combined Heat and Power in Industry and Buildings, Energy Policy, 36 (2008), 12, pp. 4522-4526
  7. Staunton, R.H., Ozpineci, B., Microturbine Power Conversion Technology Review, Department of Energy, Washington DC, USA, 2003
  8. Pilavachi, P.A., Mini- and Micro- Turbines for Combined Heat and Power, Applied Thermal Engineering, 22 (2002), 18, pp. 2003-2014
  9. Jurado, F., Modeling Micro-Turbines Using Hammerstein Models, Int. J. Energy Research, 29 (2005), 9, pp. 841-855
  10. Jurado, F., Non-Linear Modeling of Micro-Turbines Using NARX Structures on the Distribution Feeder, Int. J. Energy Conversion and Management, 46 (2005), 3, pp. 385-401
  11. Pourhasanzadeh, M., Thermodynamic Modeling and Performance Analysis of a Microturbine for Combined Heat and Power Production, Proceedings, 21st International Symposium on Transport Phenomena, Kaohsiung City, Taiwan, 2010
  12. Ehyaei, M.A., Bahadori, M.N., Selection of Micro Turbines to Meet Electrical and Thermal Energy Needs of Residential Buildings in Iran, Energy and Buildings, 39 (2007), 12, pp. 1227-1234
  13. Zaltash, A., et. al., Laboratory R&D on Integrated Energy Systems (IES), Applied Thermal Engineering, 26 (2006), 1, pp.28-35
  14. Labinov, S.D., et. al., Predictive Algorithms for Microturbine Performance for BCHP Systems, ASHRAE Transactions, 108 (2002), 2, pp. 670-681
  15. Aphornratana, S., Eames, I.W., Thermodynamic analysis of absorption refrigeration cycles using the second law of thermodynamics method, Refrigeration, 18 (1995), 4, pp. 244-252
  16. Bonnet, S., et. al., Energy, Exergy and Cost Analysis of a Micro-cogeneration System Based on an Ericsson Engine, Thermal Sciences, 44 (2005), 12, pp. 1161-1168
  17. Rivero, R., Garfias, M., Standard Chemical Exergy of Elements Updated, Energy, 31 (2006), 15, pp. 3310-3326
  18. Huang, F.F., Performance evaluation of selected combustion gas cogeneration systems based on first and second law analysis, Journal of Engineering for Gas Turbines and Power, 112 (1990), 1, pp. 117-121
  19. Cihan A., et. al., Energy-exergy Analysis and Modernization Suggestions for a Combined‐cycle Power Plant, Energy Research, 30 (2006), 2, pp. 115-126
  20. Regulagadda, P., et. al., Exergy Analysis of a Thermal Power Plant with Measured Boiler and Turbine Losses, Applied Thermal Engineering, 30 (2010), 8, pp. 970-976
  21. Valero, A., et. al., CGAM Problem: Definition and Conventional Solution, Energy, 19 (1994), 3, pp. 279-286
  22. Kotas, Tj., The Exergy Method of Thermal Plant Analysis, Butterworths, London, UK 1985
  23. Bejan, A., et. al., Thermal Design and Optimization, John Wiley and Sons Inc., New York, USA, 1996
  24. Dincer, I., Rosen, M.A., Exergy: Energy, Environment and Sustainable Development, Elsevier Ltd., 2007
  25. Gülder OL., Flame Temperature Estimation of Conventional and Future Jet Fuels, Journal of Engineering for Gas Turbine and Power, 108 (1986), 2, pp. 376-380
  26. Rizk, N.K., Mongia, H.C., Semi Analytical Correlations for NOx, CO and UHC Emissions, Journal of Engineering for Gas Turbine and Power, 115 (1993), 3, pp. 612-619
  27. Spakovsky, M.R., Application of Engineering Functional Analysis to the Analysis and Optimization of the CGAM Problem, Energy, 19 (1994), 3, pp. 343-364
  28. Pourhasanzadeh, M., Bigham, S., Optimization of a Micro Gas Turbine Using Genetic Algorithm, Proceedings, ASME Turbo Expo: Turbine Technical Conference and Exposition, Vancouver, Canada, 2011, Vol. 3, pp. 929-937
  29. Holland, J.H., Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, U Michigan Press, USA, 1975

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