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Efficient energy management of CO2 capture plant using control-based optimization approach under plant and market uncertainties

This paper employs a control-based optimization algorithm encompassing of an intelligence model predictive control (MPC) scheme and mixed integer non-linear programming (MINLP) for coal-fired power plant retrofitted with flexible solvent-based post combustion CO 2 capture (PCC) plant (integrated pla...

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Main Authors: Abdul Manaf, Norhuda, Qadir, Abdul, Abbas, Ali
Format: Article
Published: Elsevier Ltd. 2019
Subjects:
TA Engineering (General). Civil engineering (General)
Online Access:http://eprints.utm.my/id/eprint/87511/
http://dx.doi.org/10.1016/j.jprocont.2018.07.015
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spelling my.utm.875112020-11-08T04:05:29Z http://eprints.utm.my/id/eprint/87511/ Efficient energy management of CO2 capture plant using control-based optimization approach under plant and market uncertainties Abdul Manaf, Norhuda Qadir, Abdul Abbas, Ali TA Engineering (General). Civil engineering (General) This paper employs a control-based optimization algorithm encompassing of an intelligence model predictive control (MPC) scheme and mixed integer non-linear programming (MINLP) for coal-fired power plant retrofitted with flexible solvent-based post combustion CO 2 capture (PCC) plant (integrated plant). The agility and robustness of the developed control algorithm (MPC) is demonstrated through the control response time and efficiency of energy requirement including the financial and operational benefits of the plant subjected to plant and market uncertainties. While, the MINLP is utilized to forecast plant operational modes by ensuring the operational fidelity of integrated plant. This involves utilization of historical (2011) and forecast (2020) market conditions (electricity tariff and carbon price) subject to maximum plant net operating revenue. The outcomes show that the future power plant will operate in mixed operation modes, for instance in unit turndown and load following modes, which contribute to a minimum capture energy penalty at 3.13 MJ th /tonne CO 2 . Moreover, under the same year (2020), MPC exhibits superior control performance by satisfactorily obtain 94% actual CO 2 capture from the ideal cumulative CO 2 capture. Additionally, the integrated plant is capable to resume approximately 96% actual revenue from the ideal net operating revenue projected by the control-based optimization algorithm. The algorithm demonstrates that the installation of control system package (MPC) into the flexible PCC plant associated with coal-power generator could contribute to efficient energy management subjects to unprecedented uncertainties. Elsevier Ltd. 2019-02 Article PeerReviewed Abdul Manaf, Norhuda and Qadir, Abdul and Abbas, Ali (2019) Efficient energy management of CO2 capture plant using control-based optimization approach under plant and market uncertainties. Journal of Process Control, 74 . pp. 2-12. ISSN 0959-1524 http://dx.doi.org/10.1016/j.jprocont.2018.07.015 DOI:10.1016/j.jprocont.2018.07.015
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Abdul Manaf, Norhuda
Qadir, Abdul
Abbas, Ali
Efficient energy management of CO2 capture plant using control-based optimization approach under plant and market uncertainties
description This paper employs a control-based optimization algorithm encompassing of an intelligence model predictive control (MPC) scheme and mixed integer non-linear programming (MINLP) for coal-fired power plant retrofitted with flexible solvent-based post combustion CO 2 capture (PCC) plant (integrated plant). The agility and robustness of the developed control algorithm (MPC) is demonstrated through the control response time and efficiency of energy requirement including the financial and operational benefits of the plant subjected to plant and market uncertainties. While, the MINLP is utilized to forecast plant operational modes by ensuring the operational fidelity of integrated plant. This involves utilization of historical (2011) and forecast (2020) market conditions (electricity tariff and carbon price) subject to maximum plant net operating revenue. The outcomes show that the future power plant will operate in mixed operation modes, for instance in unit turndown and load following modes, which contribute to a minimum capture energy penalty at 3.13 MJ th /tonne CO 2 . Moreover, under the same year (2020), MPC exhibits superior control performance by satisfactorily obtain 94% actual CO 2 capture from the ideal cumulative CO 2 capture. Additionally, the integrated plant is capable to resume approximately 96% actual revenue from the ideal net operating revenue projected by the control-based optimization algorithm. The algorithm demonstrates that the installation of control system package (MPC) into the flexible PCC plant associated with coal-power generator could contribute to efficient energy management subjects to unprecedented uncertainties.
format Article
author Abdul Manaf, Norhuda
Qadir, Abdul
Abbas, Ali
author_facet Abdul Manaf, Norhuda
Qadir, Abdul
Abbas, Ali
author_sort Abdul Manaf, Norhuda
title Efficient energy management of CO2 capture plant using control-based optimization approach under plant and market uncertainties
title_short Efficient energy management of CO2 capture plant using control-based optimization approach under plant and market uncertainties
title_full Efficient energy management of CO2 capture plant using control-based optimization approach under plant and market uncertainties
title_fullStr Efficient energy management of CO2 capture plant using control-based optimization approach under plant and market uncertainties
title_full_unstemmed Efficient energy management of CO2 capture plant using control-based optimization approach under plant and market uncertainties
title_sort efficient energy management of co2 capture plant using control-based optimization approach under plant and market uncertainties
publisher Elsevier Ltd.
publishDate 2019
url http://eprints.utm.my/id/eprint/87511/
http://dx.doi.org/10.1016/j.jprocont.2018.07.015
_version_ 1683230776733204480
score 13.211869

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