Flexible operation of CO2 capture processes integrated with power plant using advanced control techniques

Cormoş, Ana-Maria; Vasile, Mihaela Aida; Cristea, Mircea Vasile

doi:10.1016/b978-0-444-63577-8.50103-0

Cited by 17 publications

(14 citation statements)

References 8 publications

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“…using liquid amines) or a physisorption process. Transient simulation and control of a liquid amine-based post-combustion capture system has been performed using distributed PID control [205,219,[227][228][229], cascade-PID [228], and MPC [227,[229][230][231]. Control of a post-combustion capture system based on solid sorbents has also been studied using PID control and MPC [232].…”

Section: Co 2 Capture and Sequestrationmentioning

confidence: 99%

Sustainability and process control: A survey and perspective

Daoutidis

Zachar

Jogwar

2016

Journal of Process Control

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Section: Co 2 Capture and Sequestrationmentioning

confidence: 99%

Sustainability and process control: A survey and perspective

Daoutidis

Zachar

Jogwar

2016

Journal of Process Control

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“…As mentioned before, the coal flow rate command, turbine governor valve position, power output and main steam pressure are selected as key variables for the CFPP side. For the PCC process, the lean solvent flow rate, steam flow rate to re-boiler, CO2 capture rate and re-boiler temperature are selected as the concerned variables, because they indicate the main operating status of the PCC unit and influence the CFPP operation [20]- [27]. command on the main steam pressure and power output has typical inertial characteristics, the transient process lasts for over 15 min to end the dynamics of coal feeding, pulverizing and delivering into the furnace, and combustion and heat transfer in the boiler.…”

Section: Dynamic Behavior Investigation Of the Integrated Cfpp-pcc Symentioning

confidence: 99%

“…Based on the in-depth understanding of the system dynamics, a series of control strategies were proposed for the PCC process. Four key variables were involved in most of these studies, which are CO2 capture rate, re-boiler temperature, lean solvent flow rate and re-boiler heat duty, because they are highly coupled and reflect the operation performance of the whole PCC process [20]- [27].…”

Section: Introductionmentioning

confidence: 99%

Flexible operation of coal fired power plant integrated with post combustion CO2 capture using model predictive control

Wu¹,

Wang

Shen³

et al. 2019

International Journal of Greenhouse Gas Control

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The growing demand for CO2 capture from coal-fired power plant (CFPP) has increased the need to improve the dynamic operability of the integrated power generation-CO2 capture plant. Nevertheless, high-level operation of the entire system is difficult to achieve due to the strong interactions between the CFPP and post combustion CO2 capture (PCC) unit. In addition, the control tasks of power generation and CO2 removal are in conflict, since the operation of both processes requires consuming large amount of steam. For these reasons, this paper develops a model for the integrated CFPP-PCC process and analyzes the dynamic relationships for the key variables within the integrated system. Based on the investigation, a centralized model predictive controller is developed to unify the power generation and PCC processes together, involving the key variables of the two systems and the interactions between them. Three operating modes are then studied for the predictive control system with different focuses on the overall system operation; power generation demand tracking and satisfying the CO2 capture requirement. The predictive controller can achieve a flexible operation of the integrated CFPP-PCC system and fully exert its functions in power generation and CO2 reduction.

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“…In recent years, there has been an increasing demand on the flexible operation of PCC processes [11][12][13][14][15][16][17][18][19][20]. From external perspectives, with the extensive penetration of renewable energy in the power grid, the coal-fired power plants have to change their loading rapidly over a wide range to alleviate the impact of unstable renewable power supplies and varying load demand [21].…”

Section: Introductionmentioning

confidence: 99%

“…Besides conventional PI controls, in recent years, a number of researchers have used the approach of model predictive control (MPC) for the capture process [13], [14], [17], [18], [35], [39]- [47]. The basic idea of MPC is to use an explicit process model to predict the future response of the plant and calculate the control inputs through the minimization of a dynamic objective function within the prediction horizon.…”

Section: Introductionmentioning

confidence: 99%

Dynamic behavior investigations and disturbance rejection predictive control of solvent-based post-combustion CO2 capture process

Shen

et al. 2019

Fuel

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Increasing demand for flexible operation has posed significant challenges to the control system design of solvent-based post-combustion CO2 capture (PCC) process: 1) the capture system itself has very slow dynamics; 2) in the case of wide range of operation, dynamic behavior of the PCC process will change significantly at different operating points; and 3) the frequent variation of upstream flue gas flowrate will bring in strong disturbances to the capture system. For these reasons, this paper provides a comprehensive study on the dynamic characteristics of the PCC process. The system dynamics under different CO2 capture rates, re-boiler temperatures, and flue gas flow rates are analyzed and compared through step-response tests. Based on the in-depth understanding of the system behavior, a disturbance rejection predictive controller (DRPC) is proposed for the PCC process. The predictive controller can track the desired CO2 capture rate quickly and smoothly in a wide operating range while tightly maintaining the re-boiler temperature around the optimal value. Active disturbance rejection approach is used in the predictive control design to improve the control property in the presence of dynamic variations or disturbances. The measured disturbances, such as the flue gas flow rate, is considered as an additional input in the predictive model development, so that accurate model prediction and timely control adjustment can be made once the disturbance is detected. For unmeasured disturbances, including model mismatches, plant behavior variations, etc., a disturbance observer is designed to estimate the value of disturbances. The estimated signal is then used as a compensation to the predictive control signal to remove the influence of disturbances. Simulations on a monoethanolamine (MEA) based PCC system developed on gCCS demonstrates the excellent effect of the proposed controller.

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Flexible operation of CO2 capture processes integrated with power plant using advanced control techniques

Cited by 17 publications

References 8 publications

Sustainability and process control: A survey and perspective

Sustainability and process control: A survey and perspective

Flexible operation of coal fired power plant integrated with post combustion CO2 capture using model predictive control

Dynamic behavior investigations and disturbance rejection predictive control of solvent-based post-combustion CO2 capture process

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