Distributed stochastic economic dispatch for smart grids :a model predictive control approach

Power systems have experienced several changes since smart grids and renewable resources increased their penetration. Traditionally, power systems operation has been addressed with unit commitment and economic dispatch problems that rely on a centralized operator. These operation methods are usually...

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Autores:
Velásquez Motta, Miguel Andrés
Tipo de recurso:
Doctoral thesis
Fecha de publicación:
2018
Institución:
Universidad de los Andes
Repositorio:
Séneca: repositorio Uniandes
Idioma:
eng
OAI Identifier:
oai:repositorio.uniandes.edu.co:1992/38716
Acceso en línea:
http://hdl.handle.net/1992/38716
Palabra clave:
Redes eléctricas inteligentes - Investigaciones
Distribución de energía eléctrica - Investigaciones
Programación estocástica
Ingeniería
Rights
openAccess
License
https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf
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dc.title.es_CO.fl_str_mv Distributed stochastic economic dispatch for smart grids :a model predictive control approach
title Distributed stochastic economic dispatch for smart grids :a model predictive control approach
spellingShingle Distributed stochastic economic dispatch for smart grids :a model predictive control approach
Redes eléctricas inteligentes - Investigaciones
Distribución de energía eléctrica - Investigaciones
Programación estocástica
Ingeniería
title_short Distributed stochastic economic dispatch for smart grids :a model predictive control approach
title_full Distributed stochastic economic dispatch for smart grids :a model predictive control approach
title_fullStr Distributed stochastic economic dispatch for smart grids :a model predictive control approach
title_full_unstemmed Distributed stochastic economic dispatch for smart grids :a model predictive control approach
title_sort Distributed stochastic economic dispatch for smart grids :a model predictive control approach
dc.creator.fl_str_mv Velásquez Motta, Miguel Andrés
dc.contributor.advisor.none.fl_str_mv Shahidehpour, Mohammad
Cadena Monroy, Angela Inés
Quijano Silva, Nicanor
dc.contributor.author.none.fl_str_mv Velásquez Motta, Miguel Andrés
dc.contributor.jury.none.fl_str_mv Gauthier Sellier, Alain
Gallego, Luis
dc.subject.keyword.es_CO.fl_str_mv Redes eléctricas inteligentes - Investigaciones
Distribución de energía eléctrica - Investigaciones
Programación estocástica
topic Redes eléctricas inteligentes - Investigaciones
Distribución de energía eléctrica - Investigaciones
Programación estocástica
Ingeniería
dc.subject.themes.none.fl_str_mv Ingeniería
description Power systems have experienced several changes since smart grids and renewable resources increased their penetration. Traditionally, power systems operation has been addressed with unit commitment and economic dispatch problems that rely on a centralized operator. These operation methods are usually performed on a day-ahead basis, i.e., every 24 hours. As a result of volatility in renewable resources and demand, it is better to shorten the operation period, e.g., every hour. Centralized methods might not be feasible for solving short-term economic dispatch, especially in systems with several agents. Thereby, the research questions this thesis are what method can be used for solving short-term economic dispatch in the presence of smart grid elements? Second, what models can be designed in order to optimally dispatch power plants and operate different agents in a smart grid environment? Third, how uncertainty can be considered in such models without increasing dimensionality and keeping tractability? Fourth, what is the best way to operate power systems with smart grid elements? In order to solve all these questions, we deeply analyzed economic dispatch methods and smart grid elements. Next, we proposed two distributed economic dispatch methods that are feasible for hourly and ultra-short term periods. In addition, we integrated stochastic programming through a data-driven scenario generation in order to include randomness of power system variables. Finally, a hierarchical operation of hourly and ultra-short term was proposed to enhance operation performance. The results obtained in this thesis show that proposed methods answer our research questions and serve as a basis for operating power systems more efficiently. Under uncertainty framework, it is better to use stochastic approaches rather than deterministic ones. For using stochastic approaches, it is necessary to pass from centralized controllers to distributed architectures as it has been proposed in this work
publishDate 2018
dc.date.issued.none.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2020-06-10T14:28:49Z
dc.date.available.none.fl_str_mv 2020-06-10T14:28:49Z
dc.type.spa.fl_str_mv Trabajo de grado - Doctorado
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dc.identifier.pdf.none.fl_str_mv u808376.pdf
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dc.format.extent.es_CO.fl_str_mv 130 hojas
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dc.publisher.es_CO.fl_str_mv Uniandes
dc.publisher.program.es_CO.fl_str_mv Doctorado en Ingeniería
dc.publisher.faculty.es_CO.fl_str_mv Facultad de Ingeniería
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spelling Al consultar y hacer uso de este recurso, está aceptando las condiciones de uso establecidas por los autores.https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdfinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Shahidehpour, Mohammadabe56337-8bdf-4cb5-8609-e97501b44eb4500Cadena Monroy, Angela Inés118c3e44-0fc1-42d4-8c08-e918dfdb2f58500Quijano Silva, Nicanorvirtual::13255-1Velásquez Motta, Miguel Andrés11462500Gauthier Sellier, AlainGallego, Luis2020-06-10T14:28:49Z2020-06-10T14:28:49Z2018http://hdl.handle.net/1992/3871610.57784/1992/38716u808376.pdfinstname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/Power systems have experienced several changes since smart grids and renewable resources increased their penetration. Traditionally, power systems operation has been addressed with unit commitment and economic dispatch problems that rely on a centralized operator. These operation methods are usually performed on a day-ahead basis, i.e., every 24 hours. As a result of volatility in renewable resources and demand, it is better to shorten the operation period, e.g., every hour. Centralized methods might not be feasible for solving short-term economic dispatch, especially in systems with several agents. Thereby, the research questions this thesis are what method can be used for solving short-term economic dispatch in the presence of smart grid elements? Second, what models can be designed in order to optimally dispatch power plants and operate different agents in a smart grid environment? Third, how uncertainty can be considered in such models without increasing dimensionality and keeping tractability? Fourth, what is the best way to operate power systems with smart grid elements? In order to solve all these questions, we deeply analyzed economic dispatch methods and smart grid elements. Next, we proposed two distributed economic dispatch methods that are feasible for hourly and ultra-short term periods. In addition, we integrated stochastic programming through a data-driven scenario generation in order to include randomness of power system variables. Finally, a hierarchical operation of hourly and ultra-short term was proposed to enhance operation performance. The results obtained in this thesis show that proposed methods answer our research questions and serve as a basis for operating power systems more efficiently. Under uncertainty framework, it is better to use stochastic approaches rather than deterministic ones. For using stochastic approaches, it is necessary to pass from centralized controllers to distributed architectures as it has been proposed in this workLos sistemas de energía han experimentado varios cambios debido a que las redes inteligentes y los recursos renovables han aumentado su penetración. Tradicionalmente, el funcionamiento de los sistemas de energía se ha resuelto con la técnica de Unit Commitment y despacho económico, que dependen de un operador centralizado. Estos métodos de operación generalmente se realizan con un día de anticipación, es decir, cada 24 horas. Como resultado de la volatilidad de los recursos renovables y la demanda de energía, es mejor acortar el período de operación del sistema, e.g., cada hora. Es posible que los métodos centralizados no sean factibles para resolver el despacho económico a corto plazo, especialmente en sistemas con varios agentes. De este modo, la investigación realizada en este trabajo busca resolver las siguientes preguntas: ¿qué método se puede utilizar para resolver el despacho económico a corto plazo en presencia de elementos de redes inteligentes? En segundo lugar, ¿qué modelos se pueden diseñar para despachar plantas de energía de manera óptima y operar diferentes agentes en un entorno de red inteligente? En tercer lugar, ¿cómo se puede considerar la incertidumbre en tales modelos sin aumentar la dimensionalidad y mantener la capacidad de cómputo? En cuarto lugar, ¿cuál es la mejor manera de operar sistemas de energía con elementos de redes inteligentes? Para resolver todas estas preguntas, analizamos en profundidad los métodos de despacho económico y los elementos de las redes inteligentes. Posteriormente, propusimos dos métodos distribuidos de despacho económico que son factibles para períodos de una hora y de muy corto plazo. Además, se consideró la programación estocástica a través de una generación de escenarios basada en datos históricos para incluir la aleatoriedad de las variables del sistema de potencia. Finalmente, se propuso una operación jerárquica combinando los enfoques de una hora y de muy corto plazo para mejorar la operación del sistemaDoctor en IngenieríaDoctorado130 hojasapplication/pdfengUniandesDoctorado en IngenieríaFacultad de Ingenieríainstname:Universidad de los Andesreponame:Repositorio Institucional SénecaDistributed stochastic economic dispatch for smart grids :a model predictive control approachTrabajo de grado - Doctoradoinfo:eu-repo/semantics/doctoralThesishttp://purl.org/coar/resource_type/c_db06http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/TDRedes eléctricas inteligentes - InvestigacionesDistribución de energía eléctrica - InvestigacionesProgramación estocásticaIngenieríaPublicationhttps://scholar.google.es/citations?user=xu0jdYAAAAAJvirtual::13255-10000-0002-8688-3195virtual::13255-1https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000849669virtual::13255-1698e35fc-6e9e-4c84-8960-ae30da9bc64avirtual::13255-1698e35fc-6e9e-4c84-8960-ae30da9bc64avirtual::13255-1TEXTu808376.pdf.txtu808376.pdf.txtExtracted texttext/plain227064https://repositorio.uniandes.edu.co/bitstreams/002d3d73-b3b6-486c-a7f1-ac0959552262/download66e5c0b30d330a8ff1344a884a9b9490MD54ORIGINALu808376.pdfapplication/pdf2195998https://repositorio.uniandes.edu.co/bitstreams/f48a3e13-bb0a-408b-a45e-230338a65ebf/download8813684226429826cb841739fba8384aMD51THUMBNAILu808376.pdf.jpgu808376.pdf.jpgIM Thumbnailimage/jpeg10709https://repositorio.uniandes.edu.co/bitstreams/d42d3052-cfcd-454b-9aad-9a3fe8b26d84/download849b3f317ede39550f2688b9f0bea9cdMD551992/38716oai:repositorio.uniandes.edu.co:1992/387162024-08-26 15:25:27.892https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdfopen.accesshttps://repositorio.uniandes.edu.coRepositorio institucional Sénecaadminrepositorio@uniandes.edu.co