Abstract
The estimation of the optimum number of loops to operate an integrated solar combined cycle gas turbine (ISCC) represents a complex problem and a very time demanding operation, which must be calculated in near-real time and as a result, it is hardly possible to be solved with regular ISCC production models. This problem is addressed evaluating different soft computing techniques, concluding that the BAG-REPT metamodel fits best generating MAE test of 4.19% and RMSE test of 8.75%. This model presents much lower time than regular ISCC production models and might be used as a decision tool for feasibility assessments and also in pre-design stages of new ISCC projects.
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References
Baghernejad, A., Yaghoubi, M.: Exergy analysis of an integrated solar combined cycle system. Renewable Energy 35, 2157–2164 (2010)
Antonanzas-Torres, F., Sodupe-Ortega, E., Sanz-Garcia, A., Fernandez-Martinez, R., Martinez-de-Pison-Ascacibar, F.J.: Technical feasibility assessment of integrated solar combined cycle power plants in Ciudad Real (Spain) and Las Vegas (USA). In: Proc. 16th International Congress on Project Engineering, Valencia, Spain (2012)
NREL, National Renewable Energy Laboratory (2013), http://www.nrel.gov/csp/solarpaces/
Sanz-Garcia, A., Antonanzas-Torres, F., Fernandez-Ceniceros, J., Martinez-de-Pison, F.J.: Overall models based on ensemble methods for predicting continuous annealing furnace temperature settings. Ironmaking and Steelmaking (2013), doi:10.1179/1743281213Y.0000000104
de Oliveira Penna Tavares, G., Pacheco, M.A.C.: A Genetic algorithm applied to a main sequence stellar model. In: Corchado, E., Kurzyński, M., Woźniak, M. (eds.) HAIS 2011, Part I. LNCS (LNAI), vol. 6678, pp. 32–42. Springer, Heidelberg (2011)
Pop, P.C., Matei, O., Sitar, C.P., Chira, C.: A genetic algorithm for solving the generalized vehicle routing problem. In: Corchado, E., Graña Romay, M., Manhaes Savio, A. (eds.) HAIS 2010, Part II. LNCS (LNAI), vol. 6077, pp. 119–126. Springer, Heidelberg (2010)
Martinez-de-Pison, F.J., Pernia, A.V., Blanco, J., Gonzalez, A., Lostado, R.: Control model for an elastomer extrusion process obtained via a comparative analysis of data mining and artificial intelligence techniques. Polymer-Plastics Technology and Engineering 49, 779–790 (2010)
Martinez-de-Pison, F.J., Pernia, A.V., Gonzalez, A., Lopez-Ochoa, L.M., Ordieres, J.B.: Optimum model for predicting temperature settings on hot dip galvanising line. Ironmaking and Steelmaking 37(3), 187–194 (2010)
Akaike, H.: A new look at the statistical model identification. IEEE Transactions on Automatic Control 16, 716–723 (1974)
Cover, T., Hart, P.: Nearest neighbor pattern classification. IEEE Transactions on Information Theory 13, 21–27 (1967)
Wang, Y., Witten, I.H.: Induction of model trees for predicting continuous classes. In: Proc. 9th European Conference on Machine Learning, Prague, Czech Republic, pp. 128–137 (April 1997)
Breiman, L.: Bagging predictors. Machine Learning 24, 123–140 (1996)
Stochastic gradient boosting. Stanford University, Standford (1999)
Mckay, M., Beckman, R., Conover, W.: A comparison of three method for selecting values of input variables in the analysis of output from a computer code. Tecnometrics 21, 239–245 (1979)
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Antoñanzas-Torres, J., Antoñanzas-Torres, F., Sodupe-Ortega, E., Martínez-de-Pisón, F.J. (2014). Optimization of Solar Integration in Combined Cycle Gas Turbines (ISCC). In: Herrero, Á., et al. International Joint Conference SOCO’13-CISIS’13-ICEUTE’13. Advances in Intelligent Systems and Computing, vol 239. Springer, Cham. https://doi.org/10.1007/978-3-319-01854-6_4
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DOI: https://doi.org/10.1007/978-3-319-01854-6_4
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