Modeling CO2 Recovery for Optimal Dynamic Operations

Ricardo DUNIA; Gary T. ROCHELLE; S. Joe QIN

doi:10.1109/CDC.2011.6160356

Modeling CO2 Recovery for Optimal Dynamic Operations

Ricardo DUNIA^*
, Gary T. ROCHELLE
, S. Joe QIN

^*Corresponding author for this work

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Referred Conference Paper › peer-review

4 Citations (Scopus)

Abstract

The development of amine scrubbing processes for coal and natural gas-fired power plants is essential to reduce CO₂ emissions. The design of tailor-made dynamic models to predict CO₂ capture in amine scrubbing processes is fundamental for optimal control operations. This paper presents the use of SIMPCA, a subspace system identification technique used to develop a dynamic empirical model for an LQG controller with integral action. Such a controller is made to attain optimal operating conditions for a CO₂ capture pilot plant. Reference signals are used in conjunction with the controller integral action to bring few process outputs towards their set-points. The results illustrate the importance of reliable model prediction in order to provide desirable closed loop response and appropriate CO₂ emission reduction. © 2011 IEEE.

Original language	English
Title of host publication	2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
Publisher	Institute of Electrical and Electronics Engineers
Pages	6475-6480
Number of pages	6
ISBN (Electronic)	9781612848013
ISBN (Print)	9781612848006
DOIs	https://doi.org/10.1109/CDC.2011.6160356
Publication status	Published - Dec 2011
Externally published	Yes
Event	50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 - Orlando, United States Duration: 12 Dec 2011 → 15 Dec 2011

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Publisher	Institute of Electrical and Electronics Engineers
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
Country/Territory	United States
City	Orlando
Period	12/12/11 → 15/12/11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action

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10.1109/CDC.2011.6160356

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DUNIA, R., ROCHELLE, G. T., & QIN, S. J. (2011). Modeling CO2 Recovery for Optimal Dynamic Operations. In 2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 (pp. 6475-6480). Article 6160356 (Proceedings of the IEEE Conference on Decision and Control). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CDC.2011.6160356

@inproceedings{b08f10586ae142a2842f1cfa847d6807,

title = "Modeling CO2 Recovery for Optimal Dynamic Operations",

abstract = "The development of amine scrubbing processes for coal and natural gas-fired power plants is essential to reduce CO2 emissions. The design of tailor-made dynamic models to predict CO2 capture in amine scrubbing processes is fundamental for optimal control operations. This paper presents the use of SIMPCA, a subspace system identification technique used to develop a dynamic empirical model for an LQG controller with integral action. Such a controller is made to attain optimal operating conditions for a CO2 capture pilot plant. Reference signals are used in conjunction with the controller integral action to bring few process outputs towards their set-points. The results illustrate the importance of reliable model prediction in order to provide desirable closed loop response and appropriate CO2 emission reduction. {\textcopyright} 2011 IEEE.",

author = "Ricardo DUNIA and ROCHELLE, \{Gary T.\} and QIN, \{S. Joe\}",

year = "2011",

month = dec,

doi = "10.1109/CDC.2011.6160356",

language = "English",

isbn = "9781612848006",

series = "Proceedings of the IEEE Conference on Decision and Control",

publisher = "Institute of Electrical and Electronics Engineers",

pages = "6475--6480",

booktitle = "2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011",

address = "United States",

note = "50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 ; Conference date: 12-12-2011 Through 15-12-2011",

}

DUNIA, R, ROCHELLE, GT & QIN, SJ 2011, Modeling CO2 Recovery for Optimal Dynamic Operations. in 2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011., 6160356, Proceedings of the IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers, pp. 6475-6480, 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011, Orlando, Florida, United States, 12/12/11. https://doi.org/10.1109/CDC.2011.6160356

Modeling CO2 Recovery for Optimal Dynamic Operations. / DUNIA, Ricardo; ROCHELLE, Gary T.; QIN, S. Joe.
2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011. Institute of Electrical and Electronics Engineers, 2011. p. 6475-6480 6160356 (Proceedings of the IEEE Conference on Decision and Control).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Referred Conference Paper › peer-review

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T1 - Modeling CO2 Recovery for Optimal Dynamic Operations

AU - DUNIA, Ricardo

AU - ROCHELLE, Gary T.

AU - QIN, S. Joe

PY - 2011/12

Y1 - 2011/12

N2 - The development of amine scrubbing processes for coal and natural gas-fired power plants is essential to reduce CO2 emissions. The design of tailor-made dynamic models to predict CO2 capture in amine scrubbing processes is fundamental for optimal control operations. This paper presents the use of SIMPCA, a subspace system identification technique used to develop a dynamic empirical model for an LQG controller with integral action. Such a controller is made to attain optimal operating conditions for a CO2 capture pilot plant. Reference signals are used in conjunction with the controller integral action to bring few process outputs towards their set-points. The results illustrate the importance of reliable model prediction in order to provide desirable closed loop response and appropriate CO2 emission reduction. © 2011 IEEE.

AB - The development of amine scrubbing processes for coal and natural gas-fired power plants is essential to reduce CO2 emissions. The design of tailor-made dynamic models to predict CO2 capture in amine scrubbing processes is fundamental for optimal control operations. This paper presents the use of SIMPCA, a subspace system identification technique used to develop a dynamic empirical model for an LQG controller with integral action. Such a controller is made to attain optimal operating conditions for a CO2 capture pilot plant. Reference signals are used in conjunction with the controller integral action to bring few process outputs towards their set-points. The results illustrate the importance of reliable model prediction in order to provide desirable closed loop response and appropriate CO2 emission reduction. © 2011 IEEE.

UR - https://www.scopus.com/pages/publications/84860653915

U2 - 10.1109/CDC.2011.6160356

DO - 10.1109/CDC.2011.6160356

M3 - Conference paper (refereed)

SN - 9781612848006

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 6475

EP - 6480

BT - 2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011

PB - Institute of Electrical and Electronics Engineers

T2 - 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011

Y2 - 12 December 2011 through 15 December 2011

ER -

Modeling CO2 Recovery for Optimal Dynamic Operations

Abstract

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UN SDGs

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