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Energies
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Modelling, Optimization and Control of Carbon Capture for Power Plants
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Modelling, Optimization and Control of Carbon Capture for Power Plants

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "B: Energy and Environment".

Deadline for manuscript submissions: closed (15 July 2022) | Viewed by 8529

Special Issue Editors

Dr. Xiao Wu

E-Mail Website
Guest Editor
National Engineering Research Center of Power Generation Control and Safety, School of Energy and Environment, Southeast University, Nanjing 210096, China
Interests: optimization and control of low-carbon energy system
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Meihong Wang

E-Mail Website
Guest Editor
Department of Chemical and Biological Engineering, University of Sheffield, Sheffield S1 3JD, S Yorkshire, UK
Interests: process modelling/simulation; process optimisation; process control; carbon capture, utilisation and storage (CCUS); energy storage; bioenergy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The decarbonisation of the power energy sector in the world economy is vital for meeting the goal of low carbon emissions. In spite of the rapid development of renewable power, conventional thermal power plants still meet around 60% of the world’s power consumption, and this situation will not change quickly because many thermal power plants have been developed since 2005 and could continue to serve for another three to four decades. Carbon capture is thereby viewed as a medium-term solution to transition the current fossil-fuel-based energy system to one that has near-zero CO­2 emissions. However, the lower economic benefits raise concerns about its expansion. Optimization of the carbon capture system by developing new solvents, modifying the process configurations and finding economical design and operating parameters is therefore needed to improve the process efficiency.

On the other hand, the increasingly high penetration of renewable energies raises urgent flexibility requirements for integrated power generation–carbon capture units. Consequently, control problems in dealing with issues such as nonlinearity over a wide operating range, time-variant behaviour and strong interactions among the multitude of variables become severe for power plant–carbon capture systems. A report from IEAGHG has thus recommended that developing dynamic models and investigating the transient characteristics of integrated power generation–carbon capture process systems should be studied to combine the operation of power plants and carbon capture.

This Special Issue will feature the most recent developments and state-of-the-art methods for the optimal operation of power plant–carbon capture units. The targeted readers include both academic researchers and industrial practitioners. The topics of interest include but are not limited to the following areas:

  • The first-principle modelling and systematic identification of carbon capture systems for power plants;
  • The optimization of the carbon capture process for higher efficiency and operational flexibility;
  • The advanced control of carbon capture systems for power plants;
  • The modelling, optimization and control of biomass-fired power plants integrated with carbon capture;
  • The state monitoring and fault diagnosis of carbon capture plants;
  • Artificial intelligence in carbon capture;
  • Projects demonstrating carbon capture for power plants.

Dr. Xiao Wu
Prof. Dr. Meihong Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Carbon capture for power plants
  • Process modelling/identification/simulation
  • Process optimization/control
  • Flexible operation
  • Artificial intelligence

Published Papers (4 papers)

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Research

21 pages, 6791 KiB  
Article
Dynamic Modeling of CO2 Absorption Process Using Hollow-Fiber Membrane Contactor in MEA Solution
by Alexandru-Constantin Bozonc, Ana-Maria Cormos, Simion Dragan, Cristian Dinca and Calin-Cristian Cormos
Energies 2022, 15(19), 7241; https://0-doi-org.brum.beds.ac.uk/10.3390/en15197241 - 02 Oct 2022
Cited by 3 | Viewed by 2030
Abstract
In this work, a comprehensive mathematical model was developed in order to evaluate the CO2 capture process in a microporous polypropylene hollow-fiber membrane countercurrent contactor, using monoethanolamine (MEA) as the chemical solvent. In terms of CO2 chemical absorption, the developed model [...] Read more.
In this work, a comprehensive mathematical model was developed in order to evaluate the CO2 capture process in a microporous polypropylene hollow-fiber membrane countercurrent contactor, using monoethanolamine (MEA) as the chemical solvent. In terms of CO2 chemical absorption, the developed model showed excellent agreement with the experimental data published in the literature for a wide range of operating conditions (R2 > 0.96), 1–2.7 L/min gas flow rates and 10–30 L/h liquid flow rates. Based on developed model, the effects of the gas flow rate, aqueous liquid absorbents’ flow rate and also inlet CO2 concentration on the removal efficiency of CO2 were determined. The % removal of CO2 increased while increasing the MEA solution flow rate; 81% of CO2 was removed at the high flow rate. The CO2 removal efficiency decreased while increasing the gas flow rate, and the residence time in the hollow-fiber membrane contactors increased when the gas flow rate was lower, reaching 97% at a gas flow rate of 1 L‧min−1. However, the effect was more pronounced while operating at high gas flow rates. Additionally, the influence of momentous operational parameters such as the number of fibers and module length on the CO2 separation efficiency was evaluated. On this basis, the developed model was also used to evaluate CO2 capture process in hollow-fiber membrane contactors in a flexible operation scenario (with variation in operating conditions) in order to predict the process parameters (liquid and gaseous flows, composition of the streams, mass transfer area, mass transfer coefficient, etc.). Full article
(This article belongs to the Special Issue Modelling, Optimization and Control of Carbon Capture for Power Plants)
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19 pages, 433 KiB  
Article
Robust Economic MPC of the Absorption Column in Post-Combustion Carbon Capture through Zone Tracking
by Benjamin Decardi-Nelson and Jinfeng Liu
Energies 2022, 15(3), 1140; https://0-doi-org.brum.beds.ac.uk/10.3390/en15031140 - 03 Feb 2022
Cited by 1 | Viewed by 1448
Abstract
Several studies have reported the importance of optimally operating the absorption column in a post-combustion CO2 capture (PCC) plant. It has been demonstrated in our previous work how economic model predictive control (EMPC) has a great potential to improve the operation of [...] Read more.
Several studies have reported the importance of optimally operating the absorption column in a post-combustion CO2 capture (PCC) plant. It has been demonstrated in our previous work how economic model predictive control (EMPC) has a great potential to improve the operation of the PCC plant. However, the use of a general economic objective such as maximizing the absorption efficiency of the column can cause EMPC to drive the state of the system close to the constraints. This may lead to solvent overcirculation and flooding, which are undesirable. In this work, we present an EMPC with zone tracking algorithm as an effective means to address this problem. The proposed control algorithm incorporates a zone tracking objective and an economic objective to form a multi-objective optimal control problem. To ensure that the zone tracking objective is achieved in the presence of model uncertainties and time-varying flue gas flow rate, we propose a method to modify the original target zone with a control invariant set. The zone modification method combines both ellipsoidal control invariant set techniques and a back-off strategy. The use of ellipsoidal control invariant sets ensure that the method is applicable to large scale systems such as the absorption column. We present several simulation case studies that demonstrate the effectiveness and applicability of the proposed control algorithm to the absorption column in a post-combustion CO2 capture plant. Full article
(This article belongs to the Special Issue Modelling, Optimization and Control of Carbon Capture for Power Plants)
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15 pages, 4850 KiB  
Article
Studies on the CO2 Capture by Coal Fly Ash Zeolites: Process Design and Simulation
by Silviya Boycheva, Ivan Marinov and Denitza Zgureva-Filipova
Energies 2021, 14(24), 8279; https://0-doi-org.brum.beds.ac.uk/10.3390/en14248279 - 08 Dec 2021
Cited by 10 | Viewed by 2415
Abstract
At present, mitigating carbon emissions from energy production and industrial processes is more relevant than ever to limit climate change. The widespread implementation of carbon capture technologies requires the development of cost-effective and selective adsorbents with high CO2 capture capacity and low [...] Read more.
At present, mitigating carbon emissions from energy production and industrial processes is more relevant than ever to limit climate change. The widespread implementation of carbon capture technologies requires the development of cost-effective and selective adsorbents with high CO2 capture capacity and low thermal recovery. Coal fly ash has been extensively studied as a raw material for the synthesis of low-cost zeolite-like adsorbents for CO2 capture. Laboratory tests for CO2 adsorption onto coal fly ash zeolites (CFAZ) reveal promising results, but detailed computational studies are required to clarify the applicability of these materials as CO2 adsorbents on a pilot and industrial scale. The present study provides results for the validation of a simulation model for the design of adsorption columns for CO2 capture on CFAZ based on the experimental equilibrium and dynamic adsorption on a laboratory scale. The simulations were performed using ProSim DAC dynamic adsorption software to study mass transfer and energy balance in the thermal swing adsorption mode and in the most widely operated adsorption unit configuration. Full article
(This article belongs to the Special Issue Modelling, Optimization and Control of Carbon Capture for Power Plants)
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15 pages, 1654 KiB  
Article
Economic Model Predictive Control for Post-Combustion CO2 Capture System Based on MEA
by Chenbin Ma, Wenzhao Zhang, Yu Zheng and Aimin An
Energies 2021, 14(23), 8160; https://0-doi-org.brum.beds.ac.uk/10.3390/en14238160 - 05 Dec 2021
Cited by 3 | Viewed by 1755
Abstract
For the post-combustion CO2 capture (PCC) system, the time variability of the economic performance is key to the production process of such an actual industrial process. However, the performance index used by the conventional model predictive control (MPC) does not reflect the [...] Read more.
For the post-combustion CO2 capture (PCC) system, the time variability of the economic performance is key to the production process of such an actual industrial process. However, the performance index used by the conventional model predictive control (MPC) does not reflect the economy of the production process, so the economic cost function is used instead of the traditional performance index to measure the economy of the production process. In this paper, a complete dynamic model of the PCC system is constructed in Aspen Plus Dynamics. The effectiveness of the model is verified by dynamic testing; subspace identification is carried out using experimental data, a state-space equation between flue gas flow and lean solvent flow; the CO2 capture rate is obtained; and dynamic models and control algorithm models of accused objects are established in Matlab/Simulink. Under the background of the environmental protection policy, an economic model predictive control (EMPC) strategy is proposed to manipulate the PCC system through seeking the optimal function of the economic performance, and the system is guaranteed to operate under the economic optimal and excellent quality of the MPC control strategy. The simulation results verify the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Modelling, Optimization and Control of Carbon Capture for Power Plants)
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