Una estrategia de participación para una planta de generación en el mercado eléctrico colombiano
Main Article Content
Keywords
Predicción de precios, redes neuronales, portafolio de optimización, modelo de Markowitz, derivados energéticos
Resumen
Este trabajo presenta una estrategia de participación y mitigación de riesgo para una planta de generación de energía eléctrica en el mercado de energía mayorista en Colombia. La estrategia es usada para optimizar la participación de la planta en el mercado de largo plazo (contratos bilaterales) y mercado spot; igualmente se utiliza para mitigar el riesgo de exposición en el mercado spot empleando derivados financieros. Resultados numéricos indican que la metodología propuesta es más eficiente que los modelos clásicos de optimización toda vez que esta propuesta considera la volatilidad intrínseca de los mercados de largo plazo y mercado spot para su formulación.
MSC:46N10, 91G10, 68T05
PACS:89.65.Gh, 07.05.Mh
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Referencias
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[25] ——. Mercado de derivados de commodities energéticos Derivex. Informaciónhistórica de precios. [Online]. Available: http://goo.gl/39XrgP
[2] F. Villada, D. Cadavid, and J. D. Molina, “Pronóstico del precio de la energía eléctrica usando redes neuronales artificiales,” Revista Facultad de Ingeniería Universidad de Antioquia, vol. 44, pp. 111–118, Jun. 2008.
[3] D. Singhal and K. S. Swarup, “Electricity price forecasting using neural networks,” Electrical Power and Energy Systems,vol. 33, no. 3, pp. 550–555, Mar. 2011.[Online]. Available:http://dx.doi.org/10.1016/j.ijepes.2010.12.009
[4] J. D. Velásquez, I. Dyner, and R. Castro, “¿Por qué es tan difícil obtene rbuenos pronósticos de los precios de electricidad en mercados competitivos?”Cuadernos de Administración Bogotá, vol. 20, no. 34, pp. 259–282, 2007. [Online]. Available: http://www.redalyc.org/articulo.oa?id=20503412
[5] F. D. Freitas, A. F. de Souza, and A. R. de Almeida, “Prediction-based portfolio optimization model using neural networks,” Neurocomputing, vol. 72,pp. 2155–2170, Jun. 2009.
[6] F. D. Freitas, A. R. de Almeida, and A. F. de Souza, “A prediction-basedportfolio optimization model,” in Fifth International Symposium On Roboticsand Automation - ISRA 2006, Hidalgo México, 2006, pp. 520–525.
[7] Y. Cao, H. He, and R. Chandramouli, “A novel portfolio optimization method for foreign currency Investment,” in Proc. Int. Joint Conf. on Neural Networks (IJCNN’09). Atlanta, GA: IEEE, 2009, pp. 435–439. [Online]. Available: http://dx.doi.org/10.1109/IJCNN.2009.5178876,
[8] O. Ustunand and R. Kasimbeyli, “Combined forecasts in portfolio optimization:A generalized approach,” Computer & Operations Research, vol. 39,no. 4, pp. 805–819, 2012. 196
[9] M. Liu and F. F. Wu, “Portfolio optimization in electricity markets,” Electric Power System Research, vol. 77, no. 8, pp. 1000–1009, Jun. 2007.
[10] C. H. Wang and K. J. Min, “Short-term electric power trading strategies for portfolio optimization,” The Engineering Economist, vol. 53, no. 4, pp.365–379, 2008.
[11] M. F. de Oliveira, G. A. B. Arfux, and R. C. G. Teive, “RiskManagement in the commercialization activity in Brazil - An approach byusing Markowitz,” in Transmission & Distribution Conf. and Exp.: LatinAmerica (TDC’06). Caracas: IEEE, 2006, pp. 1–6. [Online]. Available:http://dx.doi.org/10.1109/TDCLA.2006.311411
[12] R. Bjorgan, C. C. Liu, and J. Lawarrée, “Financial risk managementin a competitive electricity market,” IEEE Transactions on PowerSystems, vol. 14, no. 4, pp. 1285–1291, Nov. 1999. [Online]. Available:http://dx.doi.org/10.1109/59.801886
[13] R. A. Collins, “The economics of electricity hedging and proposedmodification for the futures contracts for electricity,” IEEE Transaction onPower Systems, vol. 17, no. 1, pp. 100–107, Feb. 2002. [Online]. Available:http://dx.doi.org/10.1109/59.982199
[14] E. Tanlapco, J. Lawarrée, and C. C. Liu, “Hedging with futures contractsin a deregulated electricity industry,” IEEE Transaction on Power Systems,vol. 17, no. 3, pp. 577–582, 2002.
[15] R. Dahlgren, C. C. Liu, and J. Lawarree, “Risk assessment in energy trading,”IEEE Transaction on Power Systems, vol. 18, no. 2, pp. 503–511, May 2003.[Online]. Available: http://dx.doi.org/10.1109/TPWRS.2003.810685
[16] J. D. Arias, D. F. Cardona, and H. Salazar, “Contract price of a bilateralcontract using risk assessment: with application to Colombian wholesale electricitymarket,” in 2010 IEEE ANDESCON. Bogotá: IEEE, Sep. 2010, pp. 1–5. [Online]. Available: http://dx.doi.org/10.1109/ANDESCON.2010.5633381
[17] N. P. Yu, A. Somani, and L. Tesfatsion, “Financial risk management inrestructured wholesale power markets: Concepts and tools,” in 2010 IEEE Power and Energy Society General Meeting. Minneapolis: IEEE, 2010, pp.1–8. [Online]. Available: http://dx.doi.org/10.1109/PES.2010.5589886
[18] M. T. Hagan, H. B. Demuth, and M. H. Beale, Neural Network Design. PWSPublishing, 1996.
[19] M. H. Beale, M. T. Hagan, and H. B. Demuth, Neural Network Toolbox User’sGuide R2012b. The MathWorks, Inc, 2012.
[20] H. Markowitz, “Portfolio selection,” The Journal of Finance, vol. 7, no. 1,pp. 77–91, Mar. 1952.
[21] D. G. Luenberger, Investment Science. New York Oxford: Oxford University Press, 1998.
[22] J. C. Hull, Options, Futures and other Derivatives, 6th ed. New Jersey: Prentice Hall, 2005.
[23] XM Compañía de Expertos en Mercados S.A. E.S.P. (2014) Precio Bolsa.[Online]. Available: http://goo.gl/RMYszr
[24] Derivex. Contrato futuro de energía eléctrica mensual. [Online]. Available:http://goo.gl/DexWPM
[25] ——. Mercado de derivados de commodities energéticos Derivex. Informaciónhistórica de precios. [Online]. Available: http://goo.gl/39XrgP