Impact of wind power in middle–termed hydrothermal dispatch
DOI:
https://doi.org/10.17533/udea.redin.16640Keywords:
reservoir, wind power generation, stochastic optimization, linear programming, Monte Carlo simulation, hydrothermal dispatchAbstract
This paper describes a linear programming model and Monte Carlo simulation which solve a middle-termed hydrothermal dispatch problem for three different scenarios of wind power penetration. Transmission line effects are neglected. The fuel cost in thermal plants varies in each time period. The test system has two thermal and three hydroelectric plants that can continuously operate during the twelve-months planning term. Wind generation is modeled by using Weibull Distribution Functions particular to the Colombian system, while hydro-generation is modeled by Normal Distribution Functions. Results show costs reduction for the three scenarios of wind power penetration. The main contribution of this paper is to simultaneously introduce the stochastic effect of wind and hydrology in the hydrothermal dispatch.
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J. Galvis, A. Garcés, A. Escobar. “Aplicación del algoritmo de búsqueda tabú al problema de despacho hidrotérmico”. Scientia et Technica. Vol. 29. 2005. pp. 25-30.
R. Cypser. “Computer search for economical operation of a hydrothermal electric system”. Power Apparatus and Systems, Part III. Transactions of the American Institute of Electrical Engineers. Vol. 73. 1954. pp. 1260-1267. DOI: https://doi.org/10.1109/AIEEPAS.1954.4498956
L. Söder. “Reserve margin planning in a wind-hydrothermal power system”. Power Systems, IEEE. Vol. 8. 1993. pp. 564-571. DOI: https://doi.org/10.1109/59.260826
R. de Aquino, M. Lira, J. de Oliveira, M. Carvalho, O. Neto, G. Almeida. Application of wavelet and neural network models for wind speed and power generation forecasting in a Brazilian experimental wind park. Proceedings of the International Joint Conference Neural Networks. Georgia, USA. 2009. pp. 172-178. DOI: https://doi.org/10.1109/IJCNN.2009.5178791
H. Chen, J. Wang, Y. Zhang. Economic Dispatch of Hydro-Thermal Power System with Large-Scale Wind Power Penetration. Proceedings of the Power and Energy Engineering Conference (APPEEC), AsiaPacific. Shangai, China. 2012. pp. 1-29. DOI: https://doi.org/10.1109/APPEEC.2012.6307099
B. Gorenstin, N. Campodonico, J. Costa, M. Pereira. “Stochastic optimization of a hydrothermal systema using network constrains”. IEEE. Vol. 7. 1992. pp. 497-501. DOI: https://doi.org/10.1109/59.141787
S. Soares, C. Lyra, H. Tavares. “Optimal Generation Scheduling for Hydrothermal Power Systems”. IEEE Transactions on Power Apparatus and Systems. Vol. PAS-99. 1980. pp. 1107-1118. DOI: https://doi.org/10.1109/TPAS.1980.319741
R. Jiménez, V. Paucar. Long term hydrothermal scheduling linear programming model for large scale power systems. Proceedings of the Large Engineering Systems Conference, Power Engineering. Montreal, Canada. 2007. pp. 96-100. DOI: https://doi.org/10.1109/LESCPE.2007.4437360
R. Karki, P. Hu, R. Billinton. Reliability assessment of a wind integrated hydro-thermal power system. Proceedings of the IEEE 11th International Conference, Probabilistic Methods Applied to Power Systems (PMAPS). Singapur, Singapur. 2010. pp. 1172-1177. DOI: https://doi.org/10.1109/PMAPS.2010.5528651
C. Sun, Z. Bie, G. Li, B. Hua. Analysis of wind power integration capacity in wind-hydro-thermal hybrid power system. Proceedings of the 3rd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies Europe (ISGT). Berlin, Germany. 2012. pp. 1-8. DOI: https://doi.org/10.1109/ISGTEurope.2012.6465821
Ministerio de Minas y Energía. Atlas del viento y energía eólica de Colombia. Bogotá, Colombia. 2006. pp. 7, 146.
Ministerio de Minas y Energía, UPME. Plan de expansión de referencia. Generación-Transmisión, 2009-2023. Bogotá, Colombia. 2009. pp. 23.
EPM. Parque Eólico Jepirachi. Available on: http://www.epm.com.co/site/Home/Institucional/Nuestrasplantas/Energ%c3%ada/ParqueE%c3%b3lico.aspx. Accessed: June 15, 2013.
W. Sifuentes, A. Vargas. “Hydrothermal Scheduling Using Benders Decomposition: Accelerating Techniques”. Power Systems, IEEE. Vol. 22. 2007. pp. 1351-1359. DOI: https://doi.org/10.1109/TPWRS.2007.901751
A. Helseth, G. Warland, B. Mo. Long-term hydrothermal scheduling including network constraints. Proceedings of the 7th International Conference on the European Energy Market (EEM). Madrid, Spain. 2010. pp. 1-6. DOI: https://doi.org/10.1109/EEM.2010.5558767
C. Yasar, S. Fadil. Solution to lossy short-term hydrothermal coordination problem with limited energy supply thermal units by using first order gradient method. Proceedings of the International Conference on Electrical and Electronics Engineering (ELECO). Bursa, Turkey. 2009. pp. 129-133.
D. Legalov, S. Palamarchuk. Hydro generation scheduling with electricity price calculation. Proceedings of the IEEE Power Tech Conference. St. Petersburg, Rusia. 2005. pp. 1-6. DOI: https://doi.org/10.1109/PTC.2005.4524592
X. Bai, S. Shahidehpour. “Hydrothermal scheduling by tabu search and decomposition method”. IEEE Transactions on Power Systems. Vol. 11. 1996.pp. 968-974. DOI: https://doi.org/10.1109/59.496182
D. Mejía, J. Franco, R. Gallego. “Solución al problema del despacho de energía en sistemas hidrotérmicos usando simulated annealing”. Scientia et Technica.Vol. 29. 2005. pp. 7-12.
J. Zhang, J. Wang, C. Yue. “Small PopulationBased Particle Swarm Optimization for Short-Term Hydrothermal Scheduling”. Power Systems, IEEE. Vol. 27. 2012. pp. 142-152. DOI: https://doi.org/10.1109/TPWRS.2011.2165089
D. Mejía. Coordinación hidrotérmica de sistemas eléctricos usando predicción de caudales afluentes. Tesis de maestría en Ingeniería Eléctrica. Universidad Tecnológica de Pereira. Pereira, Colombia. 2005. pp. 48-99.
ILOG. IBM log AMPL Version 12.2 User’s Guide. Available on: http://www.ampl.com/BOOKLETS/amplcplex122userguide.pdf. Accessed: July 8, 2014.
L. Escobar, A. Duque, J. Melchor, A. Escobar. “Planeamiento de sistemas de transmisión de energía eléctrica usando AMPL”. Scientia et Technica. Vol. 51. 2012. pp. 42-50.
I. Isaac, J. Areiza, J. González, H. Biechl. Long-term energetic analysis for electric expansion planning under high wind power penetration scenarios in Colombia and neighboring countries. Proceedings of the 7th International Conference on the European, Energy Market (EEM). Madrid, Spain. 2010. pp. 1-7. DOI: https://doi.org/10.1109/EEM.2010.5558754
J. Manwell, J. McGowan, A. Rogers. Wind Energy Explained. Theory, design and application. 1st ed. Ed. John Wiley & Sons, Ltd. 2002. Chichester, England. pp. 57-59. DOI: https://doi.org/10.1002/0470846127
M. Patel. Wind and solar power systems. 1st ed. Ed. CRC Press LLC. New York, USA. 1999. pp. 52-54.
Ministerio de Minas y Energía, UPME. Sistema de información eléctrico colombiano. Demanda máxima de potencia mensual 2013. Available on: http://www.upme.gov.co/GeneradorConsultas/Consulta_Indicador.aspx?IdModulo=2&ind=3. Accessed: June 27, 2013.
ISA. Dirección planeación de la operación gerencia Centro Nacional de Despacho. Documento ISA UENCND 04-053. 2004. p. 6.
G. Canavos. Probabilidad y estadística. Aplicaciones y métodos. 2nd ed. Ed. Mc Graw-Hill. México D.F., México. 1988. pp. 130-159.
A. Garcés, O. Gómez. “Solución del problema del despacho hidrotérmico mediante simulación de Monte Carlo y punto interior”. Revista Facultad de Ingeniería Universidad de Antioquia.N.º 45. 2008. pp. 132-147.
Ministerio de Minas y Energía, UPME. Proyección de demanda de energía eléctrica en Colombia. Bogotá, Colombia. 2013. Available on: http://www.siel.gov.co/siel/documentos/documentacion/Demanda/proyeccion_demanda_ee_Abr_2013.pdf. Accessed: June 20, 2013.
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