Methodology to design an optimal decision making system for the operator of a shared electric vehicle fleet providing electrical ancillary services

ilustraciones, diagramas, tablas

Autores:: Ruiz, Semaria

Tipo de recurso:: Doctoral thesis

Fecha de publicación:: 2021

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: eng

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dc.title.eng.fl_str_mv	Methodology to design an optimal decision making system for the operator of a shared electric vehicle fleet providing electrical ancillary services
dc.title.translated.spa.fl_str_mv	Metodología para diseñar un sistema óptimo de toma de decisiones para el operador de una flota de vehículos eléctricos compartidos que presta servicios auxiliares eléctricos
title	Methodology to design an optimal decision making system for the operator of a shared electric vehicle fleet providing electrical ancillary services
spellingShingle	Methodology to design an optimal decision making system for the operator of a shared electric vehicle fleet providing electrical ancillary services 620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingeniería 380 - Comercio , comunicaciones, transporte::388 - Transporte Electricity in transportation Electricidad en el transporte Batteries Degradation Nonlinear optimization Optimal control Risk aware control Robust control Vehicle-to-Grid Electric vehicles Carsharing Envejecimiento de baterías Vehículos eléctricos Optimización no lineal Control óptimo Control con aversión al riesgo Control robusto Vehículo a red Vehículos compartidos
title_short	Methodology to design an optimal decision making system for the operator of a shared electric vehicle fleet providing electrical ancillary services
title_full	Methodology to design an optimal decision making system for the operator of a shared electric vehicle fleet providing electrical ancillary services
title_fullStr	Methodology to design an optimal decision making system for the operator of a shared electric vehicle fleet providing electrical ancillary services
title_full_unstemmed	Methodology to design an optimal decision making system for the operator of a shared electric vehicle fleet providing electrical ancillary services
title_sort	Methodology to design an optimal decision making system for the operator of a shared electric vehicle fleet providing electrical ancillary services
dc.creator.fl_str_mv	Ruiz, Semaria
dc.contributor.advisor.none.fl_str_mv	Gomez-Ramirez, Danny Arlen de Jesus Hernández-Riveros, Jesús-Antonio
dc.contributor.author.none.fl_str_mv	Ruiz, Semaria
dc.subject.ddc.spa.fl_str_mv	620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingeniería 380 - Comercio , comunicaciones, transporte::388 - Transporte
topic	620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingeniería 380 - Comercio , comunicaciones, transporte::388 - Transporte Electricity in transportation Electricidad en el transporte Batteries Degradation Nonlinear optimization Optimal control Risk aware control Robust control Vehicle-to-Grid Electric vehicles Carsharing Envejecimiento de baterías Vehículos eléctricos Optimización no lineal Control óptimo Control con aversión al riesgo Control robusto Vehículo a red Vehículos compartidos
dc.subject.lemb.none.fl_str_mv	Electricity in transportation Electricidad en el transporte
dc.subject.proposal.eng.fl_str_mv	Batteries Degradation Nonlinear optimization Optimal control Risk aware control Robust control Vehicle-to-Grid Electric vehicles Carsharing
dc.subject.proposal.spa.fl_str_mv	Envejecimiento de baterías Vehículos eléctricos Optimización no lineal Control óptimo Control con aversión al riesgo Control robusto Vehículo a red Vehículos compartidos
description	ilustraciones, diagramas, tablas
publishDate	2021
dc.date.issued.none.fl_str_mv	2021-11
dc.date.accessioned.none.fl_str_mv	2022-02-14T13:59:04Z
dc.date.available.none.fl_str_mv	2022-02-14T13:59:04Z
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
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dc.identifier.uri.none.fl_str_mv	https://repositorio.unal.edu.co/handle/unal/80966
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/80966 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	Medellín - Minas - Doctorado en Ingeniería - Sistemas Energéticos
dc.publisher.department.spa.fl_str_mv	Departamento de Procesos y Energía
dc.publisher.faculty.spa.fl_str_mv	Facultad de Minas
dc.publisher.place.spa.fl_str_mv	Medellín, Colombia
dc.publisher.branch.spa.fl_str_mv	Universidad Nacional de Colombia - Sede Medellín
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spelling	Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Gomez-Ramirez, Danny Arlen de Jesus058b736ddf4a48a643083a3ef9fdb3a0600Hernández-Riveros, Jesús-Antonio79b7c8f5ace87a6856a110aebf72ff19600Ruiz, Semaria1afb5665ee107b5f38fb4a17003267b16002022-02-14T13:59:04Z2022-02-14T13:59:04Z2021-11https://repositorio.unal.edu.co/handle/unal/80966Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramas, tablasIn the recent years, the use of electric vehicles for public transport and carsharing services has spread widely in response to the needs of reducing global polluting gases emissions and decreasing vehicle ownership. However, the implementation of the electric carsharing practice still have some changes that need to be overcome, such as limitations in regulations and the low-profit margins that can be achieved by the aggregator agent that operate the fleet. Wherefore this thesis proposes to address the challenge of low profitability margins for the aggregator, giving to the electric vehicles the feature of providing power to the electrical network. It contains the developing process of a a decision making tool for the optimal operation of a fleet of electric vehicles that are used to provide carsharing services by an aggregator agent. In this case the aggregator agent also has the possibility of providing ancillary services to the power network, taking into account the degradation of the batteries and the risk in the incomes due to the variation of carsharing demand and the energy expenditure during travels. The thesis have as main contributions proposal of an aggregated energy model for an agent that operates the electric carsharing fleet, which allows the integration of transport and electrical network related variables, and the inclusion of transport variables uncertainties; and, the design of a risk-aware hierarchical decision-making system based on this model and its application to a study case in the Aburrá Valley; which allows the inclusion of different system models at each level, provides a solution computed in less than 7 seconds, and has the stability conditions necessary for future proposals of stochastic control schemes.El uso de vehículos eléctricos para el transporte público y los servicios de automóviles compartidos se ha extendido ampliamente en los últimos años, en respuesta a las necesidades de reducir las emisiones globales de gases contaminantes y disminuir la cantidad de vehículos particulares. Sin embargo, la implementación de la práctica de vehículos compartidos aún tiene algunos retos que deben superarse, como las limitaciones en las regulaciones y los bajos márgenes de ganancia que pueden lograr los agentes logísticos de la flota. En esta tesis se propone abordar el desafío de los bajos márgenes de rentabilidad para el caso de un único agente logístico en la flota, dando a los vehículos eléctricos la posibilidad de proporcionar energía a la red eléctrica; a través del desarrollo de una herramienta de toma de decisiones para la operación óptima de una flota de vehículos eléctricos que se utilizan de manera compartida, administrados por un único operador o agente logístico (agregador). Dicho agente cuenta adicionalmente con la posibilidad de proveer servicios auxiliares a la red eléctrica, teniendo en cuenta el envejecimiento de las baterías y el riesgo en las ganancias debido a la variación de la demanda del servicio de vehículo compartido y a la energía consumida en los viajes. La tesis tiene como principales aportes la propuesta de un modelo energético agregado para el operador la flota de vehículos eléctricos compartidos, que permite la integración de las variables relacionadas con el transporte, las relacionadas con la red eléctrica, y la inclusión de incertidumbres en las variables de transporte; y, el diseño de un sistema de toma de decisiones jerárquico consciente del riesgo basado en este modelo y su aplicación a un caso de estudio en el Valle de Aburrá; el cual permite la inclusión de diferentes modelos para el sistema en cada nivel de control, brinda una solución calculada en menos de 7 segundos y cuenta con las condiciones de estabilidad necesarias para futuras propuestas de esquemas de control estocástico. (Texto tomado de la fuente)DoctoradoDoctor en IngenieríaModelado Matemático para Control y Sistemas DinámicosÁrea Curricular de Ingeniería Química e Ingeniería de Petróleosxxi, 201 páginasapplication/pdfengUniversidad Nacional de ColombiaMedellín - Minas - Doctorado en Ingeniería - Sistemas EnergéticosDepartamento de Procesos y EnergíaFacultad de MinasMedellín, ColombiaUniversidad Nacional de Colombia - Sede Medellín620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingeniería380 - Comercio , comunicaciones, transporte::388 - TransporteElectricity in transportationElectricidad en el transporteBatteries DegradationNonlinear optimizationOptimal controlRisk aware controlRobust controlVehicle-to-GridElectric vehiclesCarsharingEnvejecimiento de bateríasVehículos eléctricosOptimización no linealControl óptimoControl con aversión al riesgoControl robustoVehículo a redVehículos compartidosMethodology to design an optimal decision making system for the operator of a shared electric vehicle fleet providing electrical ancillary servicesMetodología para diseñar un sistema óptimo de toma de decisiones para el operador de una flota de vehículos eléctricos compartidos que presta servicios auxiliares eléctricosTrabajo de grado - Doctoradoinfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_db06Texthttp://purl.org/redcol/resource_type/TD[1] S. 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Available: http://dx.doi.org/10.1016/j.jprocont.2014.04.023Colciencias beca 757 de 2016DAAD Research Grant (Short-Term) 57440917 (2019)InvestigadoresORIGINAL1035831711.2022.pdf1035831711.2022.pdfTesis de Doctorado en Ingeniería - Ingeniería de Sistemas Energéticosapplication/pdf5139869https://repositorio.unal.edu.co/bitstream/unal/80966/3/1035831711.2022.pdfbe9e7b8536550abdb9ce96e093206850MD53LICENSElicense.txtlicense.txttext/plain; charset=utf-84074https://repositorio.unal.edu.co/bitstream/unal/80966/4/license.txt8153f7789df02f0a4c9e079953658ab2MD54THUMBNAIL1035831711.2022.pdf.jpg1035831711.2022.pdf.jpgGenerated Thumbnailimage/jpeg4982https://repositorio.unal.edu.co/bitstream/unal/80966/5/1035831711.2022.pdf.jpg929af12aaaa2363dabd90157b1690356MD55unal/80966oai:repositorio.unal.edu.co:unal/809662023-10-13 14:08:34.246Repositorio Institucional Universidad Nacional de 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EVESURBIFBPUiBMQSBTRUNSRVRBUsONQSBHRU5FUkFMLiAqTEEgVEVTSVMgQSBQVUJMSUNBUiBERUJFIFNFUiBMQSBWRVJTScOTTiBGSU5BTCBBUFJPQkFEQS4gCgpBbCBoYWNlciBjbGljIGVuIGVsIHNpZ3VpZW50ZSBib3TDs24sIHVzdGVkIGluZGljYSBxdWUgZXN0w6EgZGUgYWN1ZXJkbyBjb24gZXN0b3MgdMOpcm1pbm9zLiBTaSB0aWVuZSBhbGd1bmEgZHVkYSBzb2JyZSBsYSBsaWNlbmNpYSwgcG9yIGZhdm9yLCBjb250YWN0ZSBjb24gZWwgYWRtaW5pc3RyYWRvciBkZWwgc2lzdGVtYS4KClVOSVZFUlNJREFEIE5BQ0lPTkFMIERFIENPTE9NQklBIC0gw5psdGltYSBtb2RpZmljYWNpw7NuIDE5LzEwLzIwMjEK

Methodology to design an optimal decision making system for the operator of a shared electric vehicle fleet providing electrical ancillary services

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