Simulation of the model predictive control applied to a combined cycle plant
Descripción del Articulo
We present the simulation of the application of the Model-based Predictive Control (MPC) of the drum level in a Combined Cycle Plant in order to minimize the time for reaching the highest capacity of plant, around 225 MW. In contrast to others control techniques, our simulation yields that the MPC h...
Autores: | , |
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Formato: | objeto de conferencia |
Fecha de Publicación: | 2016 |
Institución: | Universidad de Ciencias y Humanidades |
Repositorio: | UCH-Institucional |
Lenguaje: | inglés |
OAI Identifier: | oai:repositorio.uch.edu.pe:uch/366 |
Enlace del recurso: | http://repositorio.uch.edu.pe/handle/uch/366 https://ieeexplore.ieee.org/document/7836243 http://dx.doi.org/10.1109/ANDESCON.2016.7836243 |
Nivel de acceso: | acceso embargado |
Materia: | Combined cycle power plants Plant startup Predictive control systems Combined cycle plant Control techniques Drum Level Expected power Industrial processs Model based predictive control Reference functions Model predictive control |
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Nieto Chaupis, HuberDel Carpio Salinas, Jorge19 October 2016 through 21 October 20162019-08-25T19:02:12Z2019-08-25T19:02:12Z2016-10Nieto Chaupis, H., & Del Carpio Salinas, J. (Octubre, 2016). Simulation of the model predictive control applied to a combined cycle plant. En IEEE ANDESCON, Perú.http://repositorio.uch.edu.pe/handle/uch/366https://ieeexplore.ieee.org/document/7836243http://dx.doi.org/10.1109/ANDESCON.2016.783624310.1109/ANDESCON.2016.7836243IEEE ANDESCON2-s2.0-85015225036We present the simulation of the application of the Model-based Predictive Control (MPC) of the drum level in a Combined Cycle Plant in order to minimize the time for reaching the highest capacity of plant, around 225 MW. In contrast to others control techniques, our simulation yields that the MPC has shown capabilities as to reach its expected power in about 40 minutes before than PID, time which normally takes the whole industrial process under this control. In the present study, we have tested up to three different reference functions in order to compare performance during the drum level control. According to the simulations, the MPC working together with these reference functions is seen to be promising in the sense of providing efficiency to the plant from the startup until the time when system is reaching 225 MW. We have also calculated a minor discrepancy of order of lees than 5%.Submitted by sistemas uch (sistemas@uch.edu.pe) on 2019-08-25T19:02:12Z No. of bitstreams: 1 REPOSITORIO.pdf: 29656 bytes, checksum: 04319d67592b306412ce804f495f0004 (MD5)Made available in DSpace on 2019-08-25T19:02:12Z (GMT). No. of bitstreams: 1 REPOSITORIO.pdf: 29656 bytes, checksum: 04319d67592b306412ce804f495f0004 (MD5) Previous issue date: 2016-10IEEE Peru SectionengInstitute of Electrical and Electronics Engineers Inc.info:eu-repo/semantics/articleIEEE ANDESCON, ANDESCON 2016info:eu-repo/semantics/embargoedAccessRepositorio Institucional - UCHUniversidad de Ciencias y Humanidadesreponame:UCH-Institucionalinstname:Universidad de Ciencias y Humanidadesinstacron:UCHCombined cycle power plantsPlant startupPredictive control systemsCombined cycle plantControl techniquesDrum LevelExpected powerIndustrial processsModel based predictive controlReference functionsModel predictive controlSimulation of the model predictive control applied to a combined cycle plantinfo:eu-repo/semantics/conferenceObjectuch/366oai:repositorio.uch.edu.pe:uch/3662019-12-20 18:34:00.833Repositorio UCHuch.dspace@gmail.com |
dc.title.en_PE.fl_str_mv |
Simulation of the model predictive control applied to a combined cycle plant |
title |
Simulation of the model predictive control applied to a combined cycle plant |
spellingShingle |
Simulation of the model predictive control applied to a combined cycle plant Nieto Chaupis, Huber Combined cycle power plants Plant startup Predictive control systems Combined cycle plant Control techniques Drum Level Expected power Industrial processs Model based predictive control Reference functions Model predictive control |
title_short |
Simulation of the model predictive control applied to a combined cycle plant |
title_full |
Simulation of the model predictive control applied to a combined cycle plant |
title_fullStr |
Simulation of the model predictive control applied to a combined cycle plant |
title_full_unstemmed |
Simulation of the model predictive control applied to a combined cycle plant |
title_sort |
Simulation of the model predictive control applied to a combined cycle plant |
author |
Nieto Chaupis, Huber |
author_facet |
Nieto Chaupis, Huber Del Carpio Salinas, Jorge |
author_role |
author |
author2 |
Del Carpio Salinas, Jorge |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Nieto Chaupis, Huber Del Carpio Salinas, Jorge |
dc.subject.en.fl_str_mv |
Combined cycle power plants Plant startup Predictive control systems Combined cycle plant Control techniques Drum Level Expected power Industrial processs Model based predictive control Reference functions Model predictive control |
topic |
Combined cycle power plants Plant startup Predictive control systems Combined cycle plant Control techniques Drum Level Expected power Industrial processs Model based predictive control Reference functions Model predictive control |
description |
We present the simulation of the application of the Model-based Predictive Control (MPC) of the drum level in a Combined Cycle Plant in order to minimize the time for reaching the highest capacity of plant, around 225 MW. In contrast to others control techniques, our simulation yields that the MPC has shown capabilities as to reach its expected power in about 40 minutes before than PID, time which normally takes the whole industrial process under this control. In the present study, we have tested up to three different reference functions in order to compare performance during the drum level control. According to the simulations, the MPC working together with these reference functions is seen to be promising in the sense of providing efficiency to the plant from the startup until the time when system is reaching 225 MW. We have also calculated a minor discrepancy of order of lees than 5%. |
publishDate |
2016 |
dc.date.accessioned.none.fl_str_mv |
2019-08-25T19:02:12Z |
dc.date.available.none.fl_str_mv |
2019-08-25T19:02:12Z |
dc.date.issued.fl_str_mv |
2016-10 |
dc.type.en_PE.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
dc.identifier.citation.en_PE.fl_str_mv |
Nieto Chaupis, H., & Del Carpio Salinas, J. (Octubre, 2016). Simulation of the model predictive control applied to a combined cycle plant. En IEEE ANDESCON, Perú. |
dc.identifier.uri.none.fl_str_mv |
http://repositorio.uch.edu.pe/handle/uch/366 https://ieeexplore.ieee.org/document/7836243 http://dx.doi.org/10.1109/ANDESCON.2016.7836243 |
dc.identifier.doi.en_PE.fl_str_mv |
10.1109/ANDESCON.2016.7836243 |
dc.identifier.journal.en_PE.fl_str_mv |
IEEE ANDESCON |
dc.identifier.scopus.none.fl_str_mv |
2-s2.0-85015225036 |
identifier_str_mv |
Nieto Chaupis, H., & Del Carpio Salinas, J. (Octubre, 2016). Simulation of the model predictive control applied to a combined cycle plant. En IEEE ANDESCON, Perú. 10.1109/ANDESCON.2016.7836243 IEEE ANDESCON 2-s2.0-85015225036 |
url |
http://repositorio.uch.edu.pe/handle/uch/366 https://ieeexplore.ieee.org/document/7836243 http://dx.doi.org/10.1109/ANDESCON.2016.7836243 |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.relation.en_PE.fl_str_mv |
info:eu-repo/semantics/article |
dc.relation.ispartof.none.fl_str_mv |
IEEE ANDESCON, ANDESCON 2016 |
dc.rights.en_PE.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
dc.coverage.temporal.none.fl_str_mv |
19 October 2016 through 21 October 2016 |
dc.publisher.en_PE.fl_str_mv |
Institute of Electrical and Electronics Engineers Inc. |
dc.source.en_PE.fl_str_mv |
Repositorio Institucional - UCH Universidad de Ciencias y Humanidades |
dc.source.none.fl_str_mv |
reponame:UCH-Institucional instname:Universidad de Ciencias y Humanidades instacron:UCH |
instname_str |
Universidad de Ciencias y Humanidades |
instacron_str |
UCH |
institution |
UCH |
reponame_str |
UCH-Institucional |
collection |
UCH-Institucional |
repository.name.fl_str_mv |
Repositorio UCH |
repository.mail.fl_str_mv |
uch.dspace@gmail.com |
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1835549007328313344 |
score |
13.873067 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).