Despacho económico-ambiental de centrales de generación térmica empleando el algoritmo de optimización de Newton-Raphson

Este artículo presenta una investigación centrada en la minimización de los costos de generación y la reducción de emisiones de gases de efecto invernadero en sistemas eléctricos predominantemente térmicos, utilizando un algoritmo de optimización basado en Newton-Raphson. La metodología aplicada inv...

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Autores:: Tohapanta Quiranza, David Alejandro
Sedano Duque, Jairo Andrés

Tipo de recurso:

Fecha de publicación:: 2024

Institución:: Universidad Distrital Francisco José de Caldas

Repositorio:: RIUD: repositorio U. Distrital

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repository_id_str
dc.title.none.fl_str_mv	Despacho económico-ambiental de centrales de generación térmica empleando el algoritmo de optimización de Newton-Raphson
dc.title.titleenglish.none.fl_str_mv	Economic-environmental dispatch of thermal generation plants using the Newton-Raphson optimization algorithm
title	Despacho económico-ambiental de centrales de generación térmica empleando el algoritmo de optimización de Newton-Raphson
spellingShingle	Despacho económico-ambiental de centrales de generación térmica empleando el algoritmo de optimización de Newton-Raphson Unidad de generación térmica Despacho económico-ambiental Algoritmo de optimización de Newton-Raphson Efecto punto de válvula Balance de potencia Ingeniería Eléctrica -- Tesis y disertaciones académicas Distribución de energía eléctrica Producción de energía eléctrica Gases de invernadero Optimización matemática Thermal generation unit Economic-environmental dispatch Newton-Raphson optimization algorithm Valve point effect Power balance
title_short	Despacho económico-ambiental de centrales de generación térmica empleando el algoritmo de optimización de Newton-Raphson
title_full	Despacho económico-ambiental de centrales de generación térmica empleando el algoritmo de optimización de Newton-Raphson
title_fullStr	Despacho económico-ambiental de centrales de generación térmica empleando el algoritmo de optimización de Newton-Raphson
title_full_unstemmed	Despacho económico-ambiental de centrales de generación térmica empleando el algoritmo de optimización de Newton-Raphson
title_sort	Despacho económico-ambiental de centrales de generación térmica empleando el algoritmo de optimización de Newton-Raphson
dc.creator.fl_str_mv	Tohapanta Quiranza, David Alejandro Sedano Duque, Jairo Andrés
dc.contributor.advisor.none.fl_str_mv	Montoya Giraldo, Oscar Danilo
dc.contributor.author.none.fl_str_mv	Tohapanta Quiranza, David Alejandro Sedano Duque, Jairo Andrés
dc.contributor.orcid.none.fl_str_mv	Montoya Giraldo; Oscar Danilo [0000-0001-6051-4925]
dc.subject.none.fl_str_mv	Unidad de generación térmica Despacho económico-ambiental Algoritmo de optimización de Newton-Raphson Efecto punto de válvula Balance de potencia
topic	Unidad de generación térmica Despacho económico-ambiental Algoritmo de optimización de Newton-Raphson Efecto punto de válvula Balance de potencia Ingeniería Eléctrica -- Tesis y disertaciones académicas Distribución de energía eléctrica Producción de energía eléctrica Gases de invernadero Optimización matemática Thermal generation unit Economic-environmental dispatch Newton-Raphson optimization algorithm Valve point effect Power balance
dc.subject.lemb.none.fl_str_mv	Ingeniería Eléctrica -- Tesis y disertaciones académicas Distribución de energía eléctrica Producción de energía eléctrica Gases de invernadero Optimización matemática
dc.subject.keyword.none.fl_str_mv	Thermal generation unit Economic-environmental dispatch Newton-Raphson optimization algorithm Valve point effect Power balance
description	Este artículo presenta una investigación centrada en la minimización de los costos de generación y la reducción de emisiones de gases de efecto invernadero en sistemas eléctricos predominantemente térmicos, utilizando un algoritmo de optimización basado en Newton-Raphson. La metodología aplicada involucra la resolución del problema de despacho económico-ambiental, considerando el efecto de punto de válvula y diversas restricciones operativas de los sistemas eléctricos de potencia. Se compara el rendimiento del algoritmo de Newton-Raphson con otros algoritmos empleados en casos de estudio similares. Los resultados obtenidos a partir de estudios con sistemas de generación térmica de 3 y 10 unidades muestran que el algoritmo propuesto ofrece soluciones óptimas y superiores en comparación con otros métodos. La estrategia demuestra su efectividad al equilibrar costos de combustibles y emisiones, resolviendo eficazmente el problema de despacho económico-ambiental.
publishDate	2024
dc.date.created.none.fl_str_mv	2024-11-21
dc.date.accessioned.none.fl_str_mv	2025-03-28T18:51:36Z
dc.date.available.none.fl_str_mv	2025-03-28T18:51:36Z
dc.type.none.fl_str_mv	bachelorThesis
dc.type.coar.fl_str_mv	http://purl.org/coar/resource_type/c_7a1f
dc.type.degree.none.fl_str_mv	Producción Académica
dc.identifier.uri.none.fl_str_mv	http://hdl.handle.net/11349/94325
url	http://hdl.handle.net/11349/94325
dc.relation.references.none.fl_str_mv	S. Rajasomashekar and P. Aravindhababu, “Biogeography based optimization technique for best compromise solution of economic emission dispatch,” Swarm Evol. Comput., vol. 7, pp. 47–57, 2012, doi: https://doi.org/10.1016/j.swevo.2012.06.001. S. Duman, U. Güvenç, and N. Yörükeren, “Gravitational search algorithm for economic dispatch with valve-point effects,” Int. Rev. Electr. Eng., vol. 5, no. 6, pp. 2890–2895, 2010. X. Xia and A. M. Elaiw, “Optimal dynamic economic dispatch of generation: A review,” Electr. Power Syst. Res., vol. 80, no. 8, pp. 975–986, 2010, doi: https://doi.org/10.1016/j.epsr.2009.12.012. T. N. Malik, A. Ul Asar, M. F. Wyne, and S. Akhtar, “A new hybrid approach for the solution of nonconvex economic dispatch problem with valve-point effects,” Electr. Power Syst. Res., vol. 80, no. 9, pp. 1128–1136, 2010, doi: https://doi.org/10.1016/j.epsr.2010.03.004. F. Ruiz-Tipán and A. Valenzuela, “Literary review of economic environmental dispatch considering bibliometric analysis,” Iteckne, vol. 19, no. 1, pp. 26–38, 2021, doi: https://doi.org/10.15332/iteckne.v19i1.2631. W. Luo, X. Yu, and Y. Wei, “Solving combined economic and emission dispatch problems using reinforcement learning-based adaptive differential evolution algorithm,” Eng. Appl. Artif. Intell., vol. 126, no. PC, p. 107002, 2023, doi: https://doi.org/10.1016/j.engappai.2023.107002. Y. Yang, S. Xia, P. Huang, and J. Qian, “Energy transition: Connotations, mechanisms and effects,” Energy Strateg. Rev., vol. 52, no. January, p. 101320, 2024, doi: https://doi.org/10.1016/j.esr.2024.101320. S. Habib, M. Ahmadi Kamarposhti, H. Shokouhandeh, I. Colak, and E. M. Barhoumi, “Economic dispatch optimization considering operation cost and environmental constraints using the HBMO method,” Energy Reports, vol. 10, pp. 1718–1725, 2023, doi: https://doi.org/10.1016/j.egyr.2023.08.032. K. de J. Berrio Castro, “Método de solución para el despacho económico en línea considerando restricciones y reglas de un mercado eléctrico,” p. 95, 2016, [Online]. Available: http://www.bdigital.unal.edu.co/54139/. Y. Sharifian and H. Abdi, “Multi-area economic dispatch problem: Methods, uncertainties, and future directions,” Renew. Sustain. Energy Rev., vol. 191, p. 114093, 2024, doi: https://doi.org/10.1016/j.rser.2023.114093. C. Ortiz Rodríguez, “Algoritmos heurísticos y metaheurísticos para el problema de localización de regeneradores.,” pp. 11–26, 2010, [Online]. Available: http://eciencia.urjc.es/handle/10115/4129. J. S. Dhillon and D. P. Kothari, “Power System Optimization (2nd edition),” pp. 18–21, 2010. B. Jeddi and V. Vahidinasab, “A modified harmony search method for environmental/economic load dispatch of real-world power systems,” Energy Convers. Manag., vol. 78, pp. 661–675, 2014, doi: https://doi.org/10.1016/j.enconman.2013.11.027. B. Shaw, V. Mukherjee, and S. P. Ghoshal, “A novel opposition-based gravitational search algorithm for combined economic and emission dispatch problems of power systems,” Int. J. Electr. Power Energy Syst., vol. 35, no. 1, pp. 21–33, 2012, doi: https://doi.org/10.1016/j.ijepes.2011.08.012. K. Bhattacharjee, A. Bhattacharya, and S. Halder Nee Dey, “Solution of Economic Emission Load Dispatch problems of power systems by Real Coded Chemical Reaction algorithm,” Int. J. Electr. Power Energy Syst., vol. 59, pp. 176–187, 2014, doi: https://doi.org/10.1016/j.ijepes.2014.02.006. N. I. Nwulu and X. Xia, “Implementing a model predictive control strategy on the dynamic economic emission dispatch problem with game theory based demand response programs,” Energy, vol. 91, pp. 404–419, 2015, doi: https://doi.org/10.1016/j.energy.2015.08.042. H. Wu, H. Zhuang, W. Zhang, and M. Ding, “Electrical Power and Energy Systems Optimal allocation of microgrid considering economic dispatch based on hybrid weighted bilevel planning method and algorithm improvement,” Int. J. Electr. POWER ENERGY Syst., vol. 75, pp. 28–37, 2016, doi: https://doi.org/10.1016/j.ijepes.2015.08.011. A. Ghasemi, M. Gheydi, M. J. Golkar, and M. Eslami, “Modeling of Wind/Environment/Economic Dispatch in power system and solving via an online learning meta-heuristic method,” Appl. Soft Comput. J., vol. 43, pp. 454–468, 2016, doi: https://doi.org/10.1016/j.asoc.2016.02.046. L. Jebaraj, C. Venkatesan, I. Soubache, and C. C. A. Rajan, “Application of differential evolution algorithm in static and dynamic economic or emission dispatch problem: A review,” Renew. Sustain. Energy Rev., vol. 77, no. March, pp. 1206–1220, 2017, doi: https://doi.org/10.1016/j.rser.2017.03.097. M. Kheshti and L. Ding, “Double weighted particle swarm optimization to non-convex wind penetrated emission/economic dispatch and multiple fuel option systems,” Renew. Energy, 2018, doi: https://doi.org/10.1016/j.renene.2018.03.024. N. Karthik, A. K. Parvathy, and R. Arul, “Multi-objective economic emission dispatch using interior search algorithm,” Int. Trans. Electr. Energy Syst., vol. 29, no. 1, pp. 1–18, 2019, doi: https://doi.org/10.1002/etep.2683. G. Yuan and W. Yang, “Study on optimization of economic dispatching of electric power system based on Hybrid Intelligent Algorithms (PSO and AFSA),” Energy, vol. 183, pp. 926–935, 2019, doi: https://doi.org/10.1016/j.energy.2019.07.008. A. Srivastava and D. K. Das, “A new Kho-Kho optimization Algorithm: An application to solve combined emission economic dispatch and combined heat and power economic dispatch problem,” Eng. Appl. Artif. Intell., vol. 94, no. January, p. 103763, 2020, doi: https://doi.org/10.1016/j.engappai.2020.103763. M. 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May, p. 115205, 2021, doi: https://doi.org/10.1016/j.eswa.2021.115205. Z. Liu, Y. Liu, H. Xu, S. Liao, K. Zhu, and X. Jiang, “Dynamic economic dispatch of power system based on DDPG algorithm,” Energy Reports, vol. 8, pp. 1122–1129, 2022, doi: https://doi.org/10.1016/j.egyr.2022.02.231. M. Dashtdar et al., “Solving the environmental/economic dispatch problem using the hybrid FA-GA multi-objective algorithm,” Energy Reports, vol. 8, pp. 13766–13779, 2022, doi: https://doi.org/10.1016/j.egyr.2022.10.054. X. Yu, Y. Duan, and W. Luo, “A knee-guided algorithm to solve multi-objective economic emission dispatch problem,” Energy, vol. 259, p. 124876, 2022, doi: https://doi.org/10.1016/j.energy.2022.124876. M. H. Hassan, S. Kamel, F. Jurado, M. Ebeed, and M. F. Elnaggar, “Economic load dispatch solution of large-scale power systems using an enhanced beluga whale optimizer,” Alexandria Eng. J., vol. 72, pp. 573–591, 2023, doi: https://doi.org/10.1016/j.aej.2023.04.002. R. Sowmya, M. 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spelling	Montoya Giraldo, Oscar DaniloTohapanta Quiranza, David AlejandroSedano Duque, Jairo AndrésMontoya Giraldo; Oscar Danilo [0000-0001-6051-4925]2025-03-28T18:51:36Z2025-03-28T18:51:36Z2024-11-21http://hdl.handle.net/11349/94325Este artículo presenta una investigación centrada en la minimización de los costos de generación y la reducción de emisiones de gases de efecto invernadero en sistemas eléctricos predominantemente térmicos, utilizando un algoritmo de optimización basado en Newton-Raphson. La metodología aplicada involucra la resolución del problema de despacho económico-ambiental, considerando el efecto de punto de válvula y diversas restricciones operativas de los sistemas eléctricos de potencia. Se compara el rendimiento del algoritmo de Newton-Raphson con otros algoritmos empleados en casos de estudio similares. Los resultados obtenidos a partir de estudios con sistemas de generación térmica de 3 y 10 unidades muestran que el algoritmo propuesto ofrece soluciones óptimas y superiores en comparación con otros métodos. La estrategia demuestra su efectividad al equilibrar costos de combustibles y emisiones, resolviendo eficazmente el problema de despacho económico-ambiental.This article presents research focused on minimizing generation costs and reducing greenhouse gas emissions in predominantly thermal power systems, using a Newton-Raphson-based optimization algorithm. The applied methodology involves the resolution of the economic-environmental dispatch problem, considering the valve point effect and various operational restrictions of electrical power systems. The performance of the Newton-Raphson algorithm is compared with other algorithms used in similar case studies. The results obtained from studies with thermal generation systems of 3 and 10 units show that the proposed algorithm offers optimal and superior solutions compared to other methods. The strategy demonstrates its effectiveness by balancing fuel costs and emissions, effectively solving the economic-environmental dispatch problem.pdfUnidad de generación térmicaDespacho económico-ambientalAlgoritmo de optimización de Newton-RaphsonEfecto punto de válvulaBalance de potenciaIngeniería Eléctrica -- Tesis y disertaciones académicasDistribución de energía eléctricaProducción de energía eléctricaGases de invernaderoOptimización matemáticaThermal generation unitEconomic-environmental dispatchNewton-Raphson optimization algorithmValve point effectPower balanceDespacho económico-ambiental de centrales de generación térmica empleando el algoritmo de optimización de Newton-RaphsonEconomic-environmental dispatch of thermal generation plants using the Newton-Raphson optimization algorithmbachelorThesisProducción Académicahttp://purl.org/coar/resource_type/c_7a1fAbierto (Texto Completo)http://purl.org/coar/access_right/c_abf2S. Rajasomashekar and P. Aravindhababu, “Biogeography based optimization technique for best compromise solution of economic emission dispatch,” Swarm Evol. Comput., vol. 7, pp. 47–57, 2012, doi: https://doi.org/10.1016/j.swevo.2012.06.001.S. Duman, U. Güvenç, and N. Yörükeren, “Gravitational search algorithm for economic dispatch with valve-point effects,” Int. Rev. Electr. Eng., vol. 5, no. 6, pp. 2890–2895, 2010.X. Xia and A. M. Elaiw, “Optimal dynamic economic dispatch of generation: A review,” Electr. Power Syst. Res., vol. 80, no. 8, pp. 975–986, 2010, doi: https://doi.org/10.1016/j.epsr.2009.12.012.T. N. Malik, A. Ul Asar, M. F. Wyne, and S. Akhtar, “A new hybrid approach for the solution of nonconvex economic dispatch problem with valve-point effects,” Electr. Power Syst. Res., vol. 80, no. 9, pp. 1128–1136, 2010, doi: https://doi.org/10.1016/j.epsr.2010.03.004.F. Ruiz-Tipán and A. Valenzuela, “Literary review of economic environmental dispatch considering bibliometric analysis,” Iteckne, vol. 19, no. 1, pp. 26–38, 2021, doi: https://doi.org/10.15332/iteckne.v19i1.2631.W. Luo, X. Yu, and Y. Wei, “Solving combined economic and emission dispatch problems using reinforcement learning-based adaptive differential evolution algorithm,” Eng. Appl. Artif. Intell., vol. 126, no. PC, p. 107002, 2023, doi: https://doi.org/10.1016/j.engappai.2023.107002.Y. Yang, S. Xia, P. Huang, and J. Qian, “Energy transition: Connotations, mechanisms and effects,” Energy Strateg. Rev., vol. 52, no. January, p. 101320, 2024, doi: https://doi.org/10.1016/j.esr.2024.101320.S. Habib, M. Ahmadi Kamarposhti, H. Shokouhandeh, I. Colak, and E. M. Barhoumi, “Economic dispatch optimization considering operation cost and environmental constraints using the HBMO method,” Energy Reports, vol. 10, pp. 1718–1725, 2023, doi: https://doi.org/10.1016/j.egyr.2023.08.032.K. de J. Berrio Castro, “Método de solución para el despacho económico en línea considerando restricciones y reglas de un mercado eléctrico,” p. 95, 2016, [Online]. Available: http://www.bdigital.unal.edu.co/54139/.Y. Sharifian and H. Abdi, “Multi-area economic dispatch problem: Methods, uncertainties, and future directions,” Renew. Sustain. Energy Rev., vol. 191, p. 114093, 2024, doi: https://doi.org/10.1016/j.rser.2023.114093.C. Ortiz Rodríguez, “Algoritmos heurísticos y metaheurísticos para el problema de localización de regeneradores.,” pp. 11–26, 2010, [Online]. Available: http://eciencia.urjc.es/handle/10115/4129.J. S. Dhillon and D. P. Kothari, “Power System Optimization (2nd edition),” pp. 18–21, 2010.B. Jeddi and V. Vahidinasab, “A modified harmony search method for environmental/economic load dispatch of real-world power systems,” Energy Convers. Manag., vol. 78, pp. 661–675, 2014, doi: https://doi.org/10.1016/j.enconman.2013.11.027.B. Shaw, V. Mukherjee, and S. P. Ghoshal, “A novel opposition-based gravitational search algorithm for combined economic and emission dispatch problems of power systems,” Int. J. Electr. Power Energy Syst., vol. 35, no. 1, pp. 21–33, 2012, doi: https://doi.org/10.1016/j.ijepes.2011.08.012.K. Bhattacharjee, A. Bhattacharya, and S. Halder Nee Dey, “Solution of Economic Emission Load Dispatch problems of power systems by Real Coded Chemical Reaction algorithm,” Int. J. Electr. Power Energy Syst., vol. 59, pp. 176–187, 2014, doi: https://doi.org/10.1016/j.ijepes.2014.02.006.N. I. Nwulu and X. Xia, “Implementing a model predictive control strategy on the dynamic economic emission dispatch problem with game theory based demand response programs,” Energy, vol. 91, pp. 404–419, 2015, doi: https://doi.org/10.1016/j.energy.2015.08.042.H. Wu, H. Zhuang, W. Zhang, and M. Ding, “Electrical Power and Energy Systems Optimal allocation of microgrid considering economic dispatch based on hybrid weighted bilevel planning method and algorithm improvement,” Int. J. Electr. POWER ENERGY Syst., vol. 75, pp. 28–37, 2016, doi: https://doi.org/10.1016/j.ijepes.2015.08.011.A. Ghasemi, M. Gheydi, M. J. Golkar, and M. Eslami, “Modeling of Wind/Environment/Economic Dispatch in power system and solving via an online learning meta-heuristic method,” Appl. Soft Comput. J., vol. 43, pp. 454–468, 2016, doi: https://doi.org/10.1016/j.asoc.2016.02.046.L. Jebaraj, C. Venkatesan, I. Soubache, and C. C. A. Rajan, “Application of differential evolution algorithm in static and dynamic economic or emission dispatch problem: A review,” Renew. Sustain. Energy Rev., vol. 77, no. March, pp. 1206–1220, 2017, doi: https://doi.org/10.1016/j.rser.2017.03.097.M. Kheshti and L. Ding, “Double weighted particle swarm optimization to non-convex wind penetrated emission/economic dispatch and multiple fuel option systems,” Renew. Energy, 2018, doi: https://doi.org/10.1016/j.renene.2018.03.024.N. Karthik, A. K. Parvathy, and R. Arul, “Multi-objective economic emission dispatch using interior search algorithm,” Int. Trans. Electr. Energy Syst., vol. 29, no. 1, pp. 1–18, 2019, doi: https://doi.org/10.1002/etep.2683.G. Yuan and W. Yang, “Study on optimization of economic dispatching of electric power system based on Hybrid Intelligent Algorithms (PSO and AFSA),” Energy, vol. 183, pp. 926–935, 2019, doi: https://doi.org/10.1016/j.energy.2019.07.008.A. Srivastava and D. K. Das, “A new Kho-Kho optimization Algorithm: An application to solve combined emission economic dispatch and combined heat and power economic dispatch problem,” Eng. Appl. Artif. Intell., vol. 94, no. January, p. 103763, 2020, doi: https://doi.org/10.1016/j.engappai.2020.103763.M. 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Senthil, “Combined Economic Emission Dispatch using Evolutionary Programming Technique,” Ecot, pp. 62–66, 2010, doi: https://doi.org/10.5120/1539-142.ORIGINALSedanoDuqueJairoAndres2024.pdfSedanoDuqueJairoAndres2024.pdfapplication/pdf738555https://repository.udistrital.edu.co/bitstreams/82eb73fb-8cd5-42d8-84f0-6025cdbb3658/download3a7b8aa5179f8c15d529236d9ccd6081MD51Licencia de uso y autorizaciónLicencia de uso y autorizaciónapplication/pdf638991https://repository.udistrital.edu.co/bitstreams/1f4173bf-e917-46a9-a5b1-4bdafd17038b/download738be1d70e03a56e40b84b558477339eMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-87167https://repository.udistrital.edu.co/bitstreams/42e5658b-eccb-4406-b952-245f0ddc2c7e/download997daf6c648c962d566d7b082dac908dMD5311349/94325oai:repository.udistrital.edu.co:11349/943252025-03-28 13:51:38.95open.accesshttps://repository.udistrital.edu.coRepositorio Universidad 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

Despacho económico-ambiental de centrales de generación térmica empleando el algoritmo de optimización de Newton-Raphson

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