Operational planning of smart microgrids considering intraday markets

ilustraciones, diagramas

Autores:: Garcia Guarín, Pedro Julian

Tipo de recurso:: Doctoral thesis

Fecha de publicación:: 2022

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: eng

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repository_id_str
dc.title.eng.fl_str_mv	Operational planning of smart microgrids considering intraday markets
dc.title.translated.spa.fl_str_mv	Planificación operativa de microrredes inteligentes considerando mercados intradiarios
title	Operational planning of smart microgrids considering intraday markets
spellingShingle	Operational planning of smart microgrids considering intraday markets 330 - Economía::333 - Economía de la tierra y de la energía INTELIGENCIA ARTIFICIAL Artificial intelligence Renewable energy sources RECURSOS ENERGETICOS RENOVABLES Smart microgrid intraday markets heuristic optimization Microrredes inteligentes Mercados intradía Optimización heurística
title_short	Operational planning of smart microgrids considering intraday markets
title_full	Operational planning of smart microgrids considering intraday markets
title_fullStr	Operational planning of smart microgrids considering intraday markets
title_full_unstemmed	Operational planning of smart microgrids considering intraday markets
title_sort	Operational planning of smart microgrids considering intraday markets
dc.creator.fl_str_mv	Garcia Guarín, Pedro Julian
dc.contributor.advisor.none.fl_str_mv	Rivera Rodríguez, Sergio Raúl Álvarez Álvarez, David Leonardo
dc.contributor.author.none.fl_str_mv	Garcia Guarín, Pedro Julian
dc.contributor.researchgroup.spa.fl_str_mv	Grupo de Investigación Emc-Un
dc.subject.ddc.spa.fl_str_mv	330 - Economía::333 - Economía de la tierra y de la energía
topic	330 - Economía::333 - Economía de la tierra y de la energía INTELIGENCIA ARTIFICIAL Artificial intelligence Renewable energy sources RECURSOS ENERGETICOS RENOVABLES Smart microgrid intraday markets heuristic optimization Microrredes inteligentes Mercados intradía Optimización heurística
dc.subject.lemb.none.fl_str_mv	INTELIGENCIA ARTIFICIAL Artificial intelligence Renewable energy sources RECURSOS ENERGETICOS RENOVABLES
dc.subject.proposal.eng.fl_str_mv	Smart microgrid intraday markets heuristic optimization
dc.subject.proposal.spa.fl_str_mv	Microrredes inteligentes Mercados intradía Optimización heurística
description	ilustraciones, diagramas
publishDate	2022
dc.date.accessioned.none.fl_str_mv	2022-03-25T18:03:04Z
dc.date.available.none.fl_str_mv	2022-03-25T18:03:04Z
dc.date.issued.none.fl_str_mv	2022-03-04
dc.type.spa.fl_str_mv	Trabajo de grado - Doctorado
dc.type.driver.spa.fl_str_mv	info:eu-repo/semantics/doctoralThesis
dc.type.version.spa.fl_str_mv	info:eu-repo/semantics/acceptedVersion
dc.type.coar.spa.fl_str_mv	http://purl.org/coar/resource_type/c_db06
dc.type.content.spa.fl_str_mv	Text
dc.type.redcol.spa.fl_str_mv	http://purl.org/redcol/resource_type/TD
format	http://purl.org/coar/resource_type/c_db06
status_str	acceptedVersion
dc.identifier.uri.none.fl_str_mv	https://repositorio.unal.edu.co/handle/unal/81389
dc.identifier.instname.spa.fl_str_mv	Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv	https://repositorio.unal.edu.co/
url	https://repositorio.unal.edu.co/handle/unal/81389 https://repositorio.unal.edu.co/
identifier_str_mv	Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv	eng
language	eng
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dc.publisher.spa.fl_str_mv	Universidad Nacional de Colombia
dc.publisher.program.spa.fl_str_mv	Bogotá - Ingeniería - Doctorado en Ingeniería - Ingeniería Eléctrica
dc.publisher.department.spa.fl_str_mv	Departamento de Ingeniería Eléctrica y Electrónica
dc.publisher.faculty.spa.fl_str_mv	Facultad de Ingeniería
dc.publisher.place.spa.fl_str_mv	Bogotá, Colombia
dc.publisher.branch.spa.fl_str_mv	Universidad Nacional de Colombia - Sede Bogotá
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spelling	Atribución-NoComercial 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Rivera Rodríguez, Sergio Raúlebc09c48c256e8bad61b48321e3a32c5Álvarez Álvarez, David Leonardo727decfbace3ea4e4527bc5a09926113Garcia Guarín, Pedro Julian8838bd61593d969081fdd40e6453445cGrupo de Investigación Emc-Un2022-03-25T18:03:04Z2022-03-25T18:03:04Z2022-03-04https://repositorio.unal.edu.co/handle/unal/81389Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramasEnvironmental concerns and sustainable development promote the adoption of smart microgrids (SMGs). However, economic interests promote an increase in income, which can result in non-optimal situations, such as non-supply of demand, the formation of monopolies and the formation of essential agents to supply demand at peak times. In this context, this research analyses a SMG that negotiates energy commitments with intraday markets and binding dispatch. In the same way, this model quantifies penalties for uncertainty of renewables with intraday markets. Besides, the profits are estimated associated with managing the distributed generation, charging and discharging of energy storage systems, a battery swapping station and residential electric vehicles. This model introduces uncertainty in the operational planning problem of a SMG related to (1) renewable generation, (2) demand forecasting, (3) market price variations, (4) planning of electric vehicle trips and (5) battery demand forecast in an electric vehicle station. The literature shows that, due to the complexity of the problem, computational intelligence provides sub-optimal solutions efficiently, resulting in the development of the advanced metaheuristics called VNS-DEEPSO, which is a combination of the Variable Neighbourhood Search (VNS) and Differential Evolutionary Particle Swarm Optimization (DEEPSO) algorithms. The results show demand management strategies, such as reduction of maximum loads, demand supply restrictions satisfactorily met, market power indicators that prevent the emergence of monopolies and pivoting agents, and a greater number of intraday markets with equally time intervals spaced that show a reduction in costs due to the uncertainty of renewables. Finally, the results of this research will constitute a tool to make decisions in smart microgrids and will help to evaluate the implementation of intraday markets in future research.El desarrollo sostenible promueve la adopción de microrredes inteligentes. Sin embargo, intereses económicos estimulan el incremento de ingresos, que puede resultar en situaciones no óptimas, como el no abastecimiento de la demanda, la formación de monopolios y la formación de agentes esenciales para abastecer la demanda. En este contexto, está investigación analiza una microrred inteligente que negocia compromisos energéticos con mercados intradiarios y el despacho vinculante. De la misma manera, en este modelo se cuantifican penalidades por incertidumbre de renovables con mercados intradiarios. Además, se estiman las ganancias asociadas con la gestión de la generación distribuida, carga y descarga de sistemas de almacenamiento de energía, una estación de intercambio de baterías y vehículos eléctricos residenciales. Este modelo introduce la incertidumbre en el problema de planificación en una microrred inteligente relacionada con (1) generación renovable, (2) pronóstico de la demanda, (3) variaciones de precios de mercado, (4) planeación de viajes de vehículos eléctricos y (5) pronóstico de demanda de baterías en una estación de vehículos eléctricos. La literatura muestra que, debido a la complejidad del problema, la inteligencia computacional proporciona soluciones subóptimas de manera eficiente, lo que resulta en el desarrollo de la metaheurística avanzada, que es una combinación de los algoritmos Variable Neighborhood Search y Differential Evolutionary Particle Swarm Optimization. Los resultados evidencian estrategias de gestión de demanda como reducción de cargas máximas, las restricciones de abastecimiento de la demanda que se cumplen satisfactoriamente, indicadores de poder de mercado que evitan la aparición de monopolios y agentes pivotantes, y un mayor número de mercados intradiarios con intervalos de tiempo igualmente espaciados que demuestran una reducción de los costos por incertidumbre de generación solar. Finalmente, los resultados de esta investigación sirven para tomar decisiones en microrredes inteligentes y ayudar a evaluar la implementación de mercados intradiarios. 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Ogata, Modern control engineering. 2002.Proyecto 785ColcienciasEstudiantesORIGINALTesis1052388958.pdfTesis1052388958.pdfTesis de Doctorado en Ingeniería Eléctricaapplication/pdf3936088https://repositorio.unal.edu.co/bitstream/unal/81389/3/Tesis1052388958.pdf119c85f3e9ea45fb6910255159cdbe95MD53LICENSElicense.txtlicense.txttext/plain; charset=utf-84074https://repositorio.unal.edu.co/bitstream/unal/81389/4/license.txt8153f7789df02f0a4c9e079953658ab2MD54THUMBNAILTesis1052388958.pdf.jpgTesis1052388958.pdf.jpgGenerated Thumbnailimage/jpeg5508https://repositorio.unal.edu.co/bitstream/unal/81389/5/Tesis1052388958.pdf.jpg95cd2b6a15bc83d4c94fba3816fc40eeMD55unal/81389oai:repositorio.unal.edu.co:unal/813892024-08-05 23:10:12.067Repositorio Institucional Universidad Nacional de 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