Sistema de toma de decisiones para la ubicación, dimensionamiento y despacho óptimo de las estaciones de carga para el abastecimiento energético de un sistema de transporte eléctrico multimodal
ilustraciones, diagramas, mapas
- Autores:
-
González Alzate, Juan Pablo
- Tipo de recurso:
- Fecha de publicación:
- 2023
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/84078
- Palabra clave:
- 620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingeniería
380 - Comercio , comunicaciones, transporte::388 - Transporte
Vehículos eléctricos
Electricidad en el transporte
Electricity in transportation
Electric vehicles
Transport
Multimodal
Charging stations
Electric vehicles
Optimization
Urban traffic
Transporte
Multimodal
Estaciones de carga
Vehículos eléctricos
Optimización
Tráfico urbano
- Rights
- openAccess
- License
- Reconocimiento 4.0 Internacional
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| dc.title.spa.fl_str_mv |
Sistema de toma de decisiones para la ubicación, dimensionamiento y despacho óptimo de las estaciones de carga para el abastecimiento energético de un sistema de transporte eléctrico multimodal |
| dc.title.translated.eng.fl_str_mv |
Decision-making system for the optimal location, sizing and dispatching of charging stations for the energy supply of a multimodal electric transport system |
| title |
Sistema de toma de decisiones para la ubicación, dimensionamiento y despacho óptimo de las estaciones de carga para el abastecimiento energético de un sistema de transporte eléctrico multimodal |
| spellingShingle |
Sistema de toma de decisiones para la ubicación, dimensionamiento y despacho óptimo de las estaciones de carga para el abastecimiento energético de un sistema de transporte eléctrico multimodal 620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingeniería 380 - Comercio , comunicaciones, transporte::388 - Transporte Vehículos eléctricos Electricidad en el transporte Electricity in transportation Electric vehicles Transport Multimodal Charging stations Electric vehicles Optimization Urban traffic Transporte Multimodal Estaciones de carga Vehículos eléctricos Optimización Tráfico urbano |
| title_short |
Sistema de toma de decisiones para la ubicación, dimensionamiento y despacho óptimo de las estaciones de carga para el abastecimiento energético de un sistema de transporte eléctrico multimodal |
| title_full |
Sistema de toma de decisiones para la ubicación, dimensionamiento y despacho óptimo de las estaciones de carga para el abastecimiento energético de un sistema de transporte eléctrico multimodal |
| title_fullStr |
Sistema de toma de decisiones para la ubicación, dimensionamiento y despacho óptimo de las estaciones de carga para el abastecimiento energético de un sistema de transporte eléctrico multimodal |
| title_full_unstemmed |
Sistema de toma de decisiones para la ubicación, dimensionamiento y despacho óptimo de las estaciones de carga para el abastecimiento energético de un sistema de transporte eléctrico multimodal |
| title_sort |
Sistema de toma de decisiones para la ubicación, dimensionamiento y despacho óptimo de las estaciones de carga para el abastecimiento energético de un sistema de transporte eléctrico multimodal |
| dc.creator.fl_str_mv |
González Alzate, Juan Pablo |
| dc.contributor.advisor.none.fl_str_mv |
Espinosa Oviedo, Jairo José |
| dc.contributor.author.none.fl_str_mv |
González Alzate, Juan Pablo |
| dc.contributor.researchgroup.spa.fl_str_mv |
Grupo de Automática de la Universidad Nacional Gaunal |
| dc.contributor.orcid.spa.fl_str_mv |
Espinosa Oviedo, Jairo José [0000-0002-0969-741X] González Alzate, Juan Pablo [0000-0003-0449-4194] |
| dc.contributor.cvlac.spa.fl_str_mv |
González Alzate, Juan Pablo [0001823119] |
| 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 Vehículos eléctricos Electricidad en el transporte Electricity in transportation Electric vehicles Transport Multimodal Charging stations Electric vehicles Optimization Urban traffic Transporte Multimodal Estaciones de carga Vehículos eléctricos Optimización Tráfico urbano |
| dc.subject.lemb.spa.fl_str_mv |
Vehículos eléctricos Electricidad en el transporte |
| dc.subject.lemb.eng.fl_str_mv |
Electricity in transportation Electric vehicles |
| dc.subject.proposal.eng.fl_str_mv |
Transport Multimodal Charging stations Electric vehicles Optimization Urban traffic |
| dc.subject.proposal.spa.fl_str_mv |
Transporte Multimodal Estaciones de carga Vehículos eléctricos Optimización Tráfico urbano |
| description |
ilustraciones, diagramas, mapas |
| publishDate |
2023 |
| dc.date.accessioned.none.fl_str_mv |
2023-06-27T15:38:12Z |
| dc.date.available.none.fl_str_mv |
2023-06-27T15:38:12Z |
| dc.date.issued.none.fl_str_mv |
2023-05-17 |
| dc.type.spa.fl_str_mv |
Trabajo de grado - Maestría |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/masterThesis |
| dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
| dc.type.content.spa.fl_str_mv |
Text |
| dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/TM |
| status_str |
acceptedVersion |
| dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/84078 |
| 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/84078 https://repositorio.unal.edu.co/ |
| identifier_str_mv |
Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
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spa |
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spa |
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RedCol LaReferencia |
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Springer, 2009 Wong, P. ; Alizadeh, M.: Congestion control and pricing in a network of electric vehicle public charging stations. En: 55th Annu. Allert. Conf. Commun. Control. Comput. Allert. (2018) Xingzhen Bai, Lei Zou Hongjian Liu Qiao S. ; Alsaadi, Fuad E.: Electric vehicle charging station planning with dynamic prediction of elastic charging demand: a hybrid particle swarm optimization algorithm. En: Complex Intelligent Systems (2022) Xinmei Yuan, Guokai Hong Xueqi Huang L.: Method for evaluating the real-world driving energy consumptions of electric vehicles. En: Energy 141 (2017), p. 1955–1968 Xuewei Qi, KanokBoriboonsomsin Matthew J.: Data-driven decomposition analysis and estimation of link-level electric vehicle energy consumption under realworld traffic conditions. En: Transportation Research Part D: Transport and Environment (2017), p. 0–1 Z. Moghaddam, D. H. ; Phung, Q. V.: Smart Charging Strategy for Electric Vehicle Charging Stations. En: IEEE Trans. Transp. Electrif (2017) Zhan, Dingsong CuiZhenpo WangPeng LiuShuo WangDavid G. DorrellXiaohui L.: Operation optimization approaches of electric vehicle battery swapping and charging station: A literature review. En: Energy (2022) Zhang, Wang Z. Liu P. ; Zhang, Z: Energy consumption analysis and prediction of electric vehicles based on real-world driving data. En: Applied Energy 174 (2020) Zheng, Yue Hill David J. Meng K.: Online Distributed MPC-Based Optimal Scheduling for EV Charging Stations in Distribution Systems. En: IEEE Transactions on Industrial Informatics 15 (2019), p. 638–649. – ISSN 15513203 Zonggen Yi, Peter H. B.: Adaptive multiresolution energy consumption prediction for electric vehicles. En: IEEE Transactions on Vehicular Technology 66 (2017), p. 10515–10525 |
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Facultad de Minas |
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Medellín, Colombia |
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Universidad Nacional de Colombia - Sede Medellín |
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Universidad Nacional de Colombia |
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Repositorio Institucional Universidad Nacional de Colombia |
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Reconocimiento 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Espinosa Oviedo, Jairo Joséad115e960b2989299b2018dae59e6ec2González Alzate, Juan Pablob0a1f5dbc3ce129a699124d22f4ffd94Grupo de Automática de la Universidad Nacional GaunalEspinosa Oviedo, Jairo José [0000-0002-0969-741X]González Alzate, Juan Pablo [0000-0003-0449-4194]González Alzate, Juan Pablo [0001823119]2023-06-27T15:38:12Z2023-06-27T15:38:12Z2023-05-17https://repositorio.unal.edu.co/handle/unal/84078Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramas, mapasEn esta tesis se propone un sistema de toma de decisiones para la ubicación, el dimensionamiento y el despacho óptimo de las estaciones de carga para el abastecimiento energético de un sistema de transporte eléctrico multimodal, que impacte positivamente la movilidad, el transporte y el medio ambiente. El sistema se compone por motocicletas híbridas, embarcaciones eléctricas y estaciones de carga con generación de energía fotovoltaica, respaldo energético de baterías y conexión a la red eléctrica. La ubicación y el dimensionamiento de estaciones de carga se basa en la programación lineal entera mixta (MILP por sus siglas en inglés) que integra costos de inversión, mantenimiento y energía no suministrada, perfiles de demanda, precios de energía, radiación y variables binarias que describen la carga y la descarga del respaldo energético. Además, para el desarrollo del despacho de energía en la estación de carga, se empleó un modelo discreto de predicción y se soluciona por medio del método de programación cuadrática (QP por sus siglas en inglés) para la maximización del beneficio del operador de la estación de carga. Dicha implementación requirió un software de simulación de movilidad urbana para validar el sistema de transporte eléctrico multimodal. Este software cuenta con la herramienta TraCI que permite la conexión con Python y dispone de una alta variedad de redes de tráfico de todo el mundo. Con esta herramienta se simularon 5 escenarios donde se obtuvieron ventajas a favor de los usuarios de la estación y ganancias considerables para los operadores de la estación de carga, además, los errores respecto al suministro y la demanda son menores al 1%. Además, El método óptimo propuesto para la ubicación y el dimensionamiento óptimo de estaciones, establece una cantidad de 4 estaciones de carga, cada una con 22 paneles solares y 10 puntos de carga. Así mismo, para un escenario que incluye conexión a la red eléctrica, se encontraron dimensiones para 1 día de operación de 10000 W de capacidad de la red. (Texto tomado de la fuente)In this thesis, a decision-making system is proposed for the location, sizing and optimal dispatch of charging stations for the energy supply of a multimodal electric transport system, which positively impacts mobility, transport and the environment. The system is made up of hybrid motorcycles, electric boats and charging stations with photovoltaic energy generation, battery backup energy and connection to the electricity grid. The location and sizing of charging stations is based on mixed integer linear programming (MILP) that integrates investment, maintenance and non-supplied energy costs, demand profiles, energy prices, radiation and binary variables that describe the charging and discharging of the energy backup. In addition, for the development of the energy dispatch in the charging station, a discrete prediction model was used and it is solved by means of the quadratic programming (QP) method to maximize the benefit of the station operator of load. This implementation required urban mobility simulation software to validate the multimodal electric transport system. This software has the TraCI tool that allows connection with Python and has a wide variety of traffic networks from around the world. With this tool, 5 scenarios were simulated where advantages were obtained in favor of station users and considerable profits for charging station operators with errors regarding supply and demand of less than 1%. In addition, the optimal method proposed for the location and optimal sizing of stations establishes a number of 4 charging stations, each with 22 solar panels and 10 charging points. Likewise, for a scenario that includes connection to the electrical network, dimensions were found for 1 day of operation of 10000 W of network capacity.MaestríaMagíster en Ingeniería - Automatización IndustrialEl desarrollo de esta tesis de maestría está enmarcado dentro de una aproximación metodológica cuantitativa, teórica y práctica, basada en simulación.Matemáticas aplicadasÁrea Curricular de Ingeniería Eléctrica e Ingeniería de Controlxvi, 120 páginasapplication/pdfspaUniversidad Nacional de ColombiaMedellín - Minas - Maestría en Ingeniería - Automatización IndustrialFacultad de MinasMedellín, ColombiaUniversidad Nacional de Colombia - Sede Medellín620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingeniería380 - Comercio , comunicaciones, transporte::388 - TransporteVehículos eléctricosElectricidad en el transporteElectricity in transportationElectric vehiclesTransportMultimodalCharging stationsElectric vehiclesOptimizationUrban trafficTransporteMultimodalEstaciones de cargaVehículos eléctricosOptimizaciónTráfico urbanoSistema de toma de decisiones para la ubicación, dimensionamiento y despacho óptimo de las estaciones de carga para el abastecimiento energético de un sistema de transporte eléctrico multimodalDecision-making system for the optimal location, sizing and dispatching of charging stations for the energy supply of a multimodal electric transport systemTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMRedColLaReferenciaA. 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En: IEEE Transactions on Vehicular Technology 66 (2017), p. 10515–10525Público generalLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/84078/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINAL1036668111.2023.pdf1036668111.2023.pdfTesis de Maestría en Ingeniería - Automatización Industrialapplication/pdf31310678https://repositorio.unal.edu.co/bitstream/unal/84078/2/1036668111.2023.pdfbc2239a56ada430afbc5a8e1d84bd855MD52THUMBNAIL1036668111.2023.pdf.jpg1036668111.2023.pdf.jpgGenerated Thumbnailimage/jpeg5660https://repositorio.unal.edu.co/bitstream/unal/84078/3/1036668111.2023.pdf.jpg4e6a0ba395b93c19fd9167f1a2f08e66MD53unal/84078oai:repositorio.unal.edu.co:unal/840782024-08-12 01:59:56.366Repositorio Institucional Universidad Nacional de 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