THERMAL SCIENCE

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Authors of this Paper

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Umit Unver

,

Alper Kelesoglu

,

Muhsin Kiliç

A NOVEL METHOD FOR PREDICTION OF GAS TURBINE POWER PRODUCTION: DEGREE-DAY METHOD

ABSTRACT
Gas turbines are widely used in the energy production. The quantity of the operating machines requires a special attention for prediction of power production in the energy marketing sector. Thus, the aim of this paper is to support the sector by making the prediction of power production more computable. By using the data from an operating power plant, correlation and regression analysis are performed and linear equation obtained for calculating useful power production vs atmospheric air temperature and a novel method, the gas turbine degree day method, was developed. The method has been addressed for calculating the isolation related issues for buildings so far. But in this paper, it is utilized to predict the theoretical maximum power production of the gas turbines in various climates for the first time. The results indicated that the difference of annual energy production capacity between the best and the last province options was calculated to be 7500 MWh approximately.
KEYWORDS
gas turbine, Degree Day, prediction of energy production, ambient temperature, Energy prediction
PAPER SUBMITTED: 2017-09-15
PAPER REVISED: 2017-11-05
PAPER ACCEPTED: 2017-11-10
PUBLISHED ONLINE: 2018-02-18
DOI REFERENCE: https://doi.org/10.2298/TSCI170915015U
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2018, VOLUME 22, ISSUE Supplement 3, PAGES [S809 - S817]
REFERENCES
  1. Khan, M. A., Technical and Financial Analysis of Combined Cycle Gas Turbine, Thermal Science, 17 (2013), 3, pp. 931-942
  2. Xing, F., Kumar, A., Huang Y., Chan S., Ruan, C., Gu, S., Fan, X., (2017) Flameless combustion with liquid fuel: A review focusing on fundamentals and gas turbine application. Applied Energy 193: 28-51.
  3. Chen J., Huang H., Li W., Sheng D. (2017) Peaking capacity enhancement of combined cycle power plants by inlet air cooling—Analysis of the critical value of relative humidity, Applied Thermal Engineering 114: 864-873
  4. Ehyaei, M. A., et al.: Exergetic Analysis of an Aircraft Turbojet Engine with an Afterburner, Thermal Science, 17 (2013), 4, pp. 1181-1194
  5. Grkovic, V. R.: A Method for Calculation of Forces Acting on Air Cooled Gas Turbine Blades Based On The Aerodynamic Theory, Thermal Science, 17 (2013), 2, pp. 547-554
  6. Zheshu, M., and Zhenhuan, Z., Thermodynamic modelling and efficiency analysis of a class of real indirectly fired gas turbine cycles. Thermal Science, 13 (2009), 4, pp. 41-48
  7. Ravikumar, N., Ramakrishna, K., Sitaramaraju, A.V., Thermo dynamic Analysis of Heat Recovery Steam Generator in Combined Cycle Power Plant, Thermal Science, 11 (2007), 4, pp. 143-156
  8. Polyzakis, A. L., et al., Long-Term Optimization Case Studies for Combined Heat and Power System, Thermal Science, 13 (2009), 4, pp. 49-60
  9. U. Unver, M. Kılıç, Second Law Based Thermoeconomic Analysıs Of Combined Cycle Power Plants Considerıng The Effects Of Environmental Temperature And Load Variatıons, Int. J. of Energy Research, (doi: 10.1002/er.1239) vol. 31 no. 2 , p 148-157, February 2007.
  10. Basha, M., et al., Impact of Inlet Fogging and Fuels on Power and Efficiency of Gas Turbine Plants, Thermal Science, 17 (2013), 4, pp. 1107-1117
  11. Escudero, M., et al.: Analysis of the Behaviour of Biofuel-Fired Gas Turbine Power Plants, Thermal Science, 16 (2012), 3, pp. 849-864
  12. Erans, M., et al.: Process Modelling and Techno-Economic Analysis of Natural Gas Combined Cycle Integrated With Calcium Looping, Thermal Science, 20 (2016), suppl. 1, pp. s59-s67
  13. Shamoushaki, M., Ehyaei M. A., Exergy, Economic And Environmental (3e) Analysis Of A Gas Turbine Power Plant And Optimization By Mopso Algorithm, Thermal Science, (2017), DOI:10.2298/TSCI161011091S
  14. Yazdi, B. A., et al., Optimization of Micro Combined Heat and Power Gas By Genetic Algorithm, Thermal Science, 19 (2015), 1, pp. 207-218
  15. Alus, M., et al., Optimization of the Triple-Pressure Combined Cycle Power Plant, Thermal Science, 16 (2012), 3, pp. 901-914
  16. Zadeh, M. P., Thermo-Economic-Environemtal Optimization of a Microturbine Using Genetic Algorithm. Thermal Science, 19 (2015), 2, pp. 475-487
  17. Gorji-Bandpy, M., and Goodarzian, H., Exergoeconomic optimization of gas turbine power plants operating parameters using genetic algorithms: A case study. Thermal Science, 15 (2011), 1, pp. 43-54.
  18. U. Unver, M. Kilic, "Performance Estimation of Gas Turbine System via Degree-Day Method", Part II, Energy, Progress in Exergy, Energy, and the Environment (First Published in IEEES6 Proceedings Book 2013.), İ. Dincer, A. Midilli, H. Kucuk, Eds. Springer International Publishing, 2014, pp. 553-558.
  19. Kopac, M., Hilalci, A., Effect of ambient temperature on the efficiency of the regenerative and reheat Catalagzi power plant in Turkey, Applied Thermal Engineering, 27 (2007) , pp. 1377-1385.
  20. Gvozdenac, D., et al.: Industrial Gas Turbine Operation Procedure Improvement. Thermal Science, 15(2011), 1, pp. 17-28
  21. P. Tüfekci, "Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods", Electrical Power and Energy Systems, vol. 60, pp. 126-140, September 2014.
  22. A. De Sa, and S. Al Zubaidy, "Gas turbine performance at varying ambient temperature", Applied Thermal Engineering, vol. 31, pp. 2735-2739, October 2011.
  23. Rashid, K. Kamal, T. Zafar, Z. Sheikh, A. Shah, and S. Mathavan, "Energy Prediction of a Combined Cycle Power Plant Using a Particle Swarm Optimization Trained Feed Forward Neural Network", 2015 International Conference on Mechanical Engineering, Automation and Control Systems (MEACS), Tomsk, Russian Federation December 01-04, 2015.
  24. A. A. Alsairafi, "Effects of ambient conditions on the thermodynamic performance of hybrid nuclear-combined cycle power plant", Int. J. Energy Res, vol. 37 , pp. 211-227, July 2013.
  25. S. F. Al-Fahed, F. N. Alasfour and H. K. Abdulrahim, "The effect of elevated inlet air temperature and relative humidity on cogeneration system", Int. J. Energy Res. vol. 33, pp. 1384-1394, May 2009.
  26. S. Singh, and R. Kumar, "Ambient air temperature effect on power plant performance", International Journal of Engineering Science and Technology (IJEST), vol. 4(8), pp. 3916-3923, 2012.
  27. N. Farouk, L. Sheng, and Q. Hayat, "Effect of Ambient Temperature on the Performance of Gas Turbine", International Journal of Computer Science Issues, vol. 10, Issue 1, no. 3, pp. 439-4420, January 2013.
  28. Bihari P, Gróf Gy, Gács I. Efficiency and cost modelling of thermal power plants. Thermal Science, 14 (2010), 3, pp. 821-834.
  29. F. Basrawi, T. Yamada, K. Nakanishi, and S. Naing, "Effect of ambient temperature on the performance of micro gas turbine with cogeneration system in cold region", Applied Thermal Engineering, vol. 31, pp. 1058-1067 , May 2011.
  30. Ö. Kaynakli, S. Özdemir, M. İ. Karamangil, Güneş işinimi ve duvar yönü dikkate alinarak optimum isil yalitim kalinliğinin belirlenmesi (Determination of optimum thermal insulation thickness by means of solar radiation and wall direction: In Turkish), Journal of the Faculty of Engineering and Architecture of Gazi University, vol. 27, no 2, pp. 367-374, 2012,
  31. A. Durmayaz, M. Kadıoglu, Z. Sen, An application of the degree-hours method to estimate the residential heating energy requirement and fuel consumption in Istanbul, Energy, vol. 25, pp. 1245-1256, 2000.
  32. U. Unver, M. Kilic, Influence of environmental temperature on the exergetic parameters of a combined cycle power plant. International Journal of Exergy. (doi: 10.1504/IJEX.2017.10001110 ) Vol. 22, no. 1, pp. 73-88. 2017.
  33. M. Fritz, P. D. Berger, Improving the User Experience through Practical Data Analytics, Elsevier Inc., Boston, U.S.A., 2015.
  34. J. SauroJames, R. Lewis, An introduction to correlation, regression, and ANOVA, Elsevier Inc., Boston., U.S.A., 2016.
  35. V. B. Liengme, A Guide to Microsoft Excel 2013 for Scientists and Engineers, Elsevier Inc., Boston., U.S.A., 2016
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A novel method for prediction of gas turbine power production: Degree-day method

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