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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Author: Velásquez Motta, Miguel Andrés
Format: doctoral thesis
Status:Published version
Publication Date:2018
Country:Colombia
Institution:Universidad de los Andes
Repository:Séneca: repositorio Uniandes
Language:English
OAI Identifier:oai:repositorio.uniandes.edu.co:1992/38716
Online Access:http://hdl.handle.net/1992/38716
Access Level:Open access
Keyword:Redes eléctricas inteligentes - Investigaciones
Distribución de energía eléctrica - Investigaciones
Programación estocástica
Ingeniería
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oai_identifier_str oai:repositorio.uniandes.edu.co:1992/38716
network_acronym_str CO
network_name_str Colombia
repository_id_str
dc.title.none.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
Velásquez Motta, Miguel Andrés
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.none.fl_str_mv Velásquez Motta, Miguel Andrés
author Velásquez Motta, Miguel Andrés
author_facet Velásquez Motta, Miguel Andrés
author_role author
dc.contributor.none.fl_str_mv Shahidehpour, Mohammad
Cadena Monroy, Angela Inés
Quijano Silva, Nicanor
Gauthier Sellier, Alain
Gallego, Luis
dc.subject.none.fl_str_mv Redes eléctricas inteligentes - Investigaciones
Distribución de energía eléctrica - Investigaciones
Programación estocástica
Ingeniería
topic Redes eléctricas inteligentes - Investigaciones
Distribución de energía eléctrica - Investigaciones
Programación estocástica
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.none.fl_str_mv 2018
dc.type.none.fl_str_mv Trabajo de grado - Doctorado
info:eu-repo/semantics/doctoralThesis
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format doctoralThesis
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/1992/38716
10.57784/1992/38716
u808376.pdf
instname:Universidad de los Andes
reponame:Repositorio Institucional Séneca
repourl:https://repositorio.uniandes.edu.co/
url http://hdl.handle.net/1992/38716
identifier_str_mv 10.57784/1992/38716
u808376.pdf
instname:Universidad de los Andes
reponame:Repositorio Institucional Séneca
repourl:https://repositorio.uniandes.edu.co/
dc.language.none.fl_str_mv eng
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dc.format.none.fl_str_mv 130 hojas
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dc.publisher.none.fl_str_mv Uniandes
Doctorado en Ingeniería
Facultad de Ingeniería
publisher.none.fl_str_mv Uniandes
Doctorado en Ingeniería
Facultad de Ingeniería
dc.source.none.fl_str_mv reponame:Séneca: repositorio Uniandes
instname:Universidad de los Andes
instacron:Universidad de los Andes
instname_str Universidad de los Andes
instacron_str Universidad de los Andes
institution Universidad de los Andes
reponame_str Séneca: repositorio Uniandes
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spelling Distributed stochastic economic dispatch for smart grids :a model predictive control approachVelásquez Motta, Miguel AndrésRedes eléctricas inteligentes - InvestigacionesDistribución de energía eléctrica - InvestigacionesProgramación estocásticaIngenieríaPower 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 IngenieríaDoctoradoUniandesDoctorado en IngenieríaFacultad de IngenieríaShahidehpour, MohammadCadena Monroy, Angela InésQuijano Silva, NicanorGauthier Sellier, AlainGallego, Luis2018Trabajo de grado - Doctoradoinfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_db06http://purl.org/coar/version/c_ab4af688f83e57aaTexthttp://purl.org/redcol/resource_type/TD130 hojasapplication/pdfapplication/pdfhttp://hdl.handle.net/1992/3871610.57784/1992/38716u808376.pdfinstname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/reponame:Séneca: repositorio Uniandesinstname:Universidad de los Andesinstacron:Universidad de los AndesengAl 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_abf22024-08-26T15:25:27Z
score 15,812429

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