Post-combustion CO2 Capture Plant Research Articles

Vapor absorption, compression and cascade heat pumps for carbon capture plants: Multi-criteria analysis and techno-economic assessment with different working fluids

Post-combustion CO2 capture plants include high costs that are associated with intense energy consumption. Heat pumps can recover heat from the flue gas and other sources in the CO2 emitting plant and upgrade it to reduce the use of fossil-based steam. The few studies regarding heat pumps in CO2 capture systems include arbitrary selection among limited working fluids, without optimizing the underlying cycle. This work implements a multi-criteria investigation of the performance of 20 working fluids for vapor compression heat pumps (VCHP) and 21 refrigerant/absorber pairs for absorption heat transformers (AHT), considering the operating optimization of each cycle for each fluid. A cascade cycle combining the two configurations (AHT-VCHP) is proposed, using the optimum fluids cyclopentane and water/potassium nitrate identified for the VCHP and the AHT. The annual operating costs are higher than the annualized capital expenditures. The proposed fluids outperform the conventional options. The VCHP with cyclopentane covers 58 % (2.68 GJ/t CO2) of the reboiler duty with recovered heat and exhibits the lowest cost of $33.8/tCO2. This is $18.7/tCO2 lower than the cost of the conventional direct contact cooling unit that is used in capture plants. The VCHP remains competitive for up to 57 % increase in the electricity price.

Sensor network design for post-combustion CO[formula omitted] capture plants: Computational efficiency and robustness

State estimation is crucial for the monitoring and control of post-combustion CO2 capture plants (PCCPs). The performance of state estimation is highly reliant on the configuration of sensors. In this work, we consider the problem of sensor selection for PCCPs and propose a computationally efficient method to determine an appropriate number of sensors and the corresponding placement of the sensors. The objective is to find the (near-)optimal set of sensors that provides the maximum degree of observability for state estimation while satisfying the budget constraint. Specifically, we resort to the information in the sensitivity matrix calculated around the operating region of a PCCP to quantify the degree of observability of the entire system corresponding to the placed sensors. The sensor selection problem is converted to an optimization problem and is efficiently solved by a one-by-one removal approach through sensitivity analysis. Next, we extend our approach to study the fault tolerance of the selected sensors to sensor malfunction. The robust sensor selection problem is to find a sensor network that gives good estimation performance even when some of the sensors fail, thereby improving the overall system robustness. The robust sensor selection problem is formulated as a max–min optimization problem. We show how the proposed approach can be adapted to solve the sensor selection max–min optimization problem. By implementing the proposed approaches, the sensor network is configured for the PCCP efficiently.

Exergy and economic analysis of the trade-off for design of post-combustion CO2 capture plant by chemical absorption with MEA

CO2 abatement strategies are crucial in any industrial cluster. In post-combustion capture solutions, the high-energy consumption and the cost associated with the operation are the main drawbacks. In this work, a chemical absorption system using a 30% MEA solution was modeled to process 3,240 t/h of flue gases with 12% CO2 content, and evaluated for design insights and their potential cost reduction and fewer energy losses, thus providing a screening tool for design and scale-up. Thermodynamic analysis showed that regulating the inlet temperature of the stripper column was pivotal in decreasing exergy destruction and heat consumption. A trade-off analysis allowed tracing their influence on system metrics, with absorber parameters being critical. Nevertheless, minimizing the Levelized Cost of CO2 Capture proved to be a more suitable metric for decision-making compared to either heat consumption or exergy efficiency. Solutions were ranked based on TOPSIS tool, which confirmed the most relevant design parameters. The potential operational expense savings (20 USD/t CO2), and thermodynamic improvement (52%), were achieved. Although capture cost values are within the expected industrial range for mature capture technologies (70 USD/t CO2), these are still far away from current taxes and levers for curbing emissions.

Impact of high capture rates and solvent and emission management strategies on the costs of full-scale post-combustion CO2 capture plants using long-term pilot plant data

Pilot plant campaigns are critical to our understanding of the performance of solvent-based post-combustion capture processes. During the ALIGN-CCUS project, long-term pilot plant runs in the Niederaussem lignite-fired power plant were conducted, that aimed to investigate solvent degradation and emissions management and capture rates beyond 90%. Based on these pilot runs, we here investigated the cost effect of amine degradation and emissions for two solvent systems, MEA and CESAR1, as well as the effect of incorporating degradation and emission mitigation strategies and the effect of higher carbon capture rates. We found that for lignite-fired power plants, CESAR1 is not per se a cheaper solvent system than MEA when actual solvent losses (or their mitigation measures) are considered, contrary to what earlier studies have suggested. It may, therefore, be just as good a benchmark as MEA would be, as long as all degradation and emission (mitigation) costs are included in their cost estimates. Second, MEA reclaiming with ion exchange resins and CESAR1 emission mitigation measures (dry-bed and/or turbulent flue gas pre-treatment) do not increase the cost of CO2 capture or electricity. If anything, our work suggests these measures reduce costs marginally, owing to lower solvent make up, offsetting the additional capital and operational costs. Finally, the cost effect of capture rates beyond 90% proves minimal (the cost of CO2 capture and the levelized cost of electricity increase by 3% and 5%, respectively, when moving from 90% to 98% CO2 capture rate), indicating solvent-based CO2 capture may also be a useful mitigation strategy in societies transitioning towards net-zero-CO2 emissions.

Mesoporous MgO enriched in Lewis base sites as effective catalysts for efficient CO2 capture

Capturing CO2 has become increasingly important. However, wide industrial applications of conventional CO2 capture technologies are limited by their slow CO2 sorption and desorption kinetics. Accordingly, this research is designed to overcome the challenge by synthesizing mesoporous MgO nanoparticles (MgO-NPs) with a new method that uses PEG 1500 as a soft template. MgO surface structure is nonstoichiometric due to its distinctive shape; the abundant Lewis base sites provided by oxygen vacancies promote CO2 capture. Adding 2 wt % MgO-NPs to 20 wt % monoethanolamine (MEA) can increase the breakthrough time (the time with 90% CO2 capturing efficiency) by ∼3000% and can increase the CO2 absorption capacity within the breakthrough time by ∼3660%. The data suggest that MgO-NPs can accelerate the rate and increase CO2 desorption capacity by up to ∼8740% and ∼2290% at 90 °C, respectively. Also, the excellent stability of the system within 50 cycles is verified. These findings demonstrate a new strategy to innovate MEA absorbents currently widely used in commercial post-combustion CO2 capture plants.

Robust Economic MPC of the Absorption Column in Post-Combustion Carbon Capture through Zone Tracking

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.

Impact of High Capture Rates and Solvent and Emission Management Strategies on the Costs of Full-Scale Post-Combustion Co2 Capture Plants Using Long-Term Pilot Plant Data

Impact of High Capture Rates and Solvent and Emission Management Strategies on the Costs of Full-Scale Post-Combustion Co2 Capture Plants Using Long-Term Pilot Plant Data

An open-access FEED study for a post-combustion CO2 capture plant retrofit to a CCGT

An open-access FEED study for a post-combustion CO2 capture plant retrofit to a CCGT

An integrated real-time optimization, control, and estimation scheme for post-combustion CO2 capture

This study presents a novel operational scheme for post-combustion CO2 capture (PCC) plants downstream from fuel-fired power plants. The approach is comprised of real-time optimization (RTO), nonlinear model predictive control (NMPC), and moving horizon estimation (MHE) layers. These layers are integrated to operate the system economically via a new economic function that accounts for the most significant economic aspects of PCC, including the carbon economy, energy, chemical, and utility costs. The proposed approach was employed on the case study of an MEA-based PCC absorber section, which uses a mechanistic process model to provide an accurate representation of the system. The NMPC layer is novel in its ability to enable flexible control of the plant by manipulating fresh material streams to impact CO2 capture and the MHE layer is the first to provide accurate system estimates to the controller with realistically accessible measurements. The proposed scheme was subjected to a cofiring scenario, whereby the switching between two fuels (i.e., biomass and coal) is reflected in the flue gas composition. In this scenario, a ∼19% steady-state cost improvement is observed with respect to the pre-disturbance cost. Moreover, the MHE was shown to cause an acceptable ∼0.5% of performance loss in the process economics through its effect on the NMPC. The scheme was also subjected to a ±20% diurnal variation in power plant load through steps in the flue gas flowrate and was found to provide consistent steady-state economic improvements (from ∼12% cost improvement to ∼17% loss abatement) for each of the disturbances observed. Furthermore, a price variation scenario highlighted the operational dependence of the system upon changes in economic incentives via the prices. When compared to a ‘no RTO’ case, the scheme was found to yield economic improvement ranging from ∼3% to ∼14% depending on the pricing. All scenarios in the case study displayed steady-state cost savings that exceeded the energy penalty imposed on the power plant by the PCC plant. This suggests the proposed scheme is an effective framework for the economic operation of a general class of PCC plants (i.e., with different solvents, process designs and control schemes, etc.) and can help enable the viability of PCC for the continued use of fuel-firing.

Techno-economic assessment and optimization of a solar-assisted industrial post-combustion CO2 capture and utilization plant

This paper studies the techno-economic feasibility of the solar-assisted regeneration process of the largest industrial CO2 removal monoethanolamine-based plant in Iran. The plant incorporating parabolic troughs is modelled using System Advisor Model software and the weather data are derived from the European Commission’s Photovoltaic Geographical Information System. Sensitivity analyses are realized to evaluate the effect of important parameters, i.e., the solar multiple and the hours of storage, and to reveal the optimum case. The studied impacts are linked to the overall net energy generation and the levelized cost of heat (LCOH). The optimum case is found to have a solar multiple of 3.1 and 18-hours of storage, resulting in a solar share of 0.7 and a LCOH of 3.85 (¢/kWh). When compared to the base case (solar multiple of 2 and 6 h of storage), the optimum solution results in a similar LCOH but it achieves the generation of an additional 16,112 MWhth annually. The thermal energy supplied by the solar system leads to an annual reduction in the natural gas consumption of approximately 3.8 million m3 that results in a CO2 emission reduction of 7.1 kton.

Investment decision of monoethanolamine based post combustion CO2 capture plant via application of control strategies

The abatement of anthropogenic CO2 gas and extensive demand for electricity has motivated cleaner power production from fossil fuels. Monoethanolamine (MEA) based post combustion CO2 capture plant (PCC) is a promising and mature technology to realize large scale cuts in carbon emissions at national and global levels. A carbon capture plant features non-linearity and multifaceted process interactions, therefore presents operational challenges requiring robust control strategies to ensure optimal but flexible operation of the plant as it responds to variable power plant output. This paper investigates two control strategies (viz, conventional feedback (PID) control and model predictive control (MPC)) with the control objective being formulated as economic functions around CO2 emissions (US$/t-CO2) and operational cost (US$/d). This presents a management capability to the power plant operator unlike the commonly used operational (technical only) objective of maximising CO2 capture (CO2%) at a given setpoint in conjunction with plant net energy performance (EPn). This economics-based formulation in the control strategy together with a demonstrated stability analysis fits well into plant-wide control implementation of MEA based PCC plants and supports cleaner production of electricity while helping such operation economically viable. It can be seen that embedment of MPC into PCC plant features attractive economic value (positive investment decision) based on the two above criteria. Whereas, CO2 emission cost and operational cost exhibit 30% and 60% of cost saving compared with the deployment of PID controller.

An open-access, detailed description of post-combustion CO2 capture plant

Bechtel National (Reston, VA) have undertaken a FEED study for retrofitting a 2x2x1 natural gas-fired gas turbine combined cycle power plant with post-combustion carbon capture (PCC) for CO2 storage/utilization. The comprehensive programme of work covers the integration of the retrofitted carbon capture and compression plant to the combined cycle power plant, together with the detailed design of an amine-based conventional absorber-stripper scrubbing system with a non-proprietary solvent, 35% w/w MEA. Supporting studies have analysed options for single- and two-stage thermal reclaiming and also examined discrepancies between process modelling packages and the possible scope for alternative trade-offs between capital and operating costs. Given that modelling alone cannot predict commercially-important factors such as solvent management costs a long-term pilot test programme is strongly recommended, with outline details supplied for pilot size and the testing period.

Evaluation of a New Chemical Mechanism for 2-Amino-2-methyl-1-propanol in a Reactive Environment from CSIRO Smog Chamber Experiments.

Amines are considered as an emerging class of atmospheric pollutants that are of great importance to atmospheric chemistry and new particle formation. As a typical amine, 2-amino-2-methyl-1-propanol (AMP) is one of the proposed solvents for capturing CO2 from flue gas streams in amine-based post-combustion CO2 capture plants, and it is expected to result in AMP emission and secondary product formation in the atmosphere. However, the current knowledge of its atmospheric chemistry and kinetics is poorly understood, particularly in a reactive environment. In this work, we used the CSIRO smog chamber to study the photo-oxidation of AMP in the presence of volatile organic compound (VOC)-NOx surrogate mixtures over a range of initial amine concentrations. O3 formation was significantly inhibited when AMP was added to the surrogate VOC-NOx mixtures, implying that AMP could alter known atmospheric chemical reaction pathways and the prevailing reactivity. Simultaneously, a large amount of AMP-derived secondary aerosol was formed, with a considerably high aerosol mass yield (i.e., ratio of aerosol formed to reacted AMP) of 1.06 ± 0.20. Based on updated knowledge of its kinetics, oxidation pathways, and product yields, we have developed a new mechanism (designated as CSIAMP-19), integrated it into the Carbon Bond 6 (CB6) chemical mechanism, and evaluated it against available smog chamber data. Compared with the existing AMP mechanism (designated as CarterAMP-08), the modified CB6 with CSIAMP-19 mechanism improves prediction against AMP-VOC-NOx experiments across a range of initial AMP concentrations, within ±10% model error for gross ozone production. Our results contribute to scientific understanding of AMP photochemistry and to the development of the chemical mechanism of other amines. Once some potential limitations are considered, the updated AMP reaction scheme can be further embedded into the chemical transport model for regional modeling scenarios where AMP-related emissions are of concern.

Flexible operation of supercritical coal-fired power plant integrated with solvent-based CO2 capture through collaborative predictive control

This paper presents a controller design study for the supercritical coal fired power plant (CFPP) integrated with solvent-based post-combustion CO 2 capture (PCC) system. The focus of the study is on the steam drawn-off from turbine to the re-boiler, which is the key interaction between the CFPP and PCC plants. The simulation study of a 660 MW supercritical CFPP-PCC unit model has shown that the impact of re-boiler steam change on the power generation of CFPP is more than 100 times faster than that on the PCC operation. Considering this finding, a collaborative predictive control strategy is proposed for the CFPP-PCC system where the re-boiler steam flowrate is manipulated for the CFPP load ramping and then gradually set to the required value for CO 2 capture. The PCC is thereby exploited as an energy storage device, which can quickly store/release extra energy for the CFPP in addition to the primary function of carbon emission reduction. The simulation results show that the proposed collaborative predictive controller can effectively improve the load ramping performance of CFPP without much performance degradation on the PCC operation. • Collaborative predictive control strategy for the integrated CFPP-PCC system. • PCC exploited as auxiliary measure for power adjustment in addition to CO 2 capture. • Impact of re-boiler steam change on CFPP is 100 times faster than that on the PCC. • Dynamic control operating simulation of the supercritical CFPP-PCC process. • Performance of different CFPP-PCC control schemes is assessed.

Efficient decentralized control of the post combustion CO2 capture plant for flexible operation against influent flue gas disturbances

The increase and accumulation of the CO2 greenhouse gases emissions raises the society’s concern and has become a stringent environmental problem. Flue gases released by thermal power plants are important contributors to these emissions and the scientific research community firmly engaged to find efficient carbon capture solutions. The post-combustion CO2 capture using amines is a leading technology, striving to continuously increase its efficiency and reduce its associated costs. Achieving these aims is progressively dependent on the flexibility of the carbon capture plant to cope with changes in its operation due to the power plant variable loading. Control systems have the potential and are responsible for fulfilling this task. The paper presents the design and assesses the performance of a 4 × 4 proposed decentralized control system intended to reject the most challenging CO2 influent flow rate and concentration disturbances emerging from the power plant, but also to satisfy the setpoint tracking ability demand. A previously developed complex model for the absorber and desorber columns was extended with a buffer tank and a cross heat exchanger meant to reduce the interacting effects between the columns and support the control system efficiency. The model was then scaled-up with the aim of building a novel simulation tool for an industrial scale carbon capture plant. Carbon Capture rate and Energy Performance indices have been selected as main metrics for evaluating the capture plant performance. Selection of the controlled and manipulated variables was based on a process analysis and the pairing of the control loops was conducted according to the Relative Gain Array matrix. The control system disturbance rejection performance was investigated considering the influent flow rate and CO2 concentration major disturbances, either with positive and negative slope ramp signals or with periodic changes and considering different testing scenarios. Setpoint tracking of the Carbon Capture rate ability was also examined. Simulation results revealed the capability of the decentralized control system to successfully reject disturbances, demonstrating zero steady state offset, reduced overshoot and short settling time control performance. Setpoint tracking also proved to be efficient. The synergic contribution of all control loops succeeded to achieve flexible control against the action of both ramp, constant or periodic disturbances. The proposed decentralized control system showed promising perspectives for the industrial implementation.

Modelling and Simulation of the Start-Up Process of Coal Fired Power Plants with Post-Combustion CO2 Capture

A detailed model of a post-combustion CO2 capture plant (pcc-plant) is developed in the Modelica language which allows the simulation of start-up and shutdown processes. The model of the pcc-plant is coupled to a simplified model of a coal fired power plant to investigate the coupled process. To guarantee a stable and automatic operation, a sequential control for start-up and shutdown procedures is implemented in both plants. Two case studies, focussing on the pcc-plant, are subsequently performed in this contribution. In the first case study, the influence of different parameters and input variables on the start-up time is investigated in order to analyze the start-up process of the pcc-plant. The varied variables are the steam flow rate to the reboiler, the solvent flow rate and the total amount of solvent in the pcc-plant. In the second case study two different start-up control structures for the carbon capture plant are proposed and their performances are presented and compared.

Modeling and simulation of the start-up process of coal fired power plants with post-combustion CO2 capture

A detailed model of a post-combustion CO2 capture plant (pcc-plant) is developed in the Modelica® language which allows the simulation of start-up and shutdown processes. The model of the pcc-plant is coupled to a simplified model of a coal fired power plant to investigate the coupled process. To guarantee a stable and automatic operation, a sequential control for start-up and shutdown procedures is implemented in both plants. Two case studies, focussing on the pcc-plant, are subsequently performed in this contribution. In the first case study, the influence of different parameters and input variables on the start-up time is investigated in order to analyze the start-up process of the pcc-plant. The varied variables are the steam flow rate to the reboiler, the solvent flow rate and the total amount of solvent in the pcc-plant. In the second case study two different start-up control structures for the carbon capture plant are proposed and their performances are presented and compared.

Gas switching reforming for flexible power and hydrogen production to balance variable renewables

Variable renewable energy (VRE) is expected to play a major role in the decarbonization of the electricity sector. However, decarbonization via VRE requires a fleet of flexible dispatchable plants with low CO2 emissions to supply clean power during times with limited wind and sunlight. These plants will need to operate at reduced capacity factors with frequent ramps in electricity output, posing techno-economic challenges. This study therefore presents an economic assessment of a new near-zero emission power plant designed for this purpose. The gas switching reforming combined cycle (GSR-CC) plant can produce electricity during times of low VRE output and hydrogen during times of high VRE output. This product flexibility allows the plant to operate continuously, even when high VRE output makes electricity production uneconomical. Although the CO2 avoidance cost of the GSR-CC plant (€61/ton) was similar to the benchmark post-combustion CO2 capture plant under baseload operation, GSR-CC clearly outperformed the benchmark in a more realistic scenario where continued VRE expansion forces power plants into mid-load operation (45% capacity factor). In this scenario, GSR-CC promises a 5 %-point higher annualized investment return than the post-combustion benchmark. GSR-CC therefore appears to be a promising concept for a future scenario with high VRE market share and CO2 prices, provided that a large market for clean hydrogen is established.

Reinforced coordinated control of coal-fired power plant retrofitted with solvent based CO2 capture using model predictive controls

Solvent-based post-combustion CO2 capture (PCC) provides a promising technology for the CO2 removal of coal-fired power plant (CFPP). However, there are strong interactions between the CFPP and the PCC system, which makes it challenging to attain a good control for the integrated plant. The PCC system requires extraction of large amounts of steam from the intermediate/low pressure steam turbine to provide heat for solvent regeneration, which will reduce power generation. Wide-range load variation of power plant will cause strong fluctuation of the flue gas flow and brings in a significant impact on the PCC system. To overcome these issues, this paper presents a reinforced coordinated control scheme for the integrated CFPP-PCC system based on the investigation of the overall plant dynamic behavior. Two model predictive controllers are developed for the CFPP and PCC plants respectively, in which the steam flow rate to re-boiler and the flue-gas flow rate are considered as feed-forward signals to link the two systems together. Three operating modes are considered for designing the coordinated control system, which are: (1) normal operating mode; (2) rapid power load change mode; and (3) strict carbon capture mode. The proposed coordinated controller can enhance the overall performance of the CFPP-PCC plant and achieve a flexible trade-off between power generation and CO2 reduction. Simulation results on a small-scale subcritical CFPP-PCC plant developed on gCCS demonstrates the effectiveness of the proposed controller.

Dynamic Real-Time Optimisation of a CO2 Capture Facility

Abstract This work investigates economic optimisation of an energy-intensive amine regeneration process in a post-combustion CO2 capture plant, subject to a minimum CO2 capture ratio over 24 hours. A Dynamic Real-Time Optimisation algorithm is implemented as a single-level Nonlinear Model Predictive Control scheme by utilising the infeasible soft-constraint method to include economic objectives in an industrial tracking NMPC package. A time-varying price of electricity is exploited to enhance cost minimisation by adjusting the regeneration according to the peaks of the price curve. This flexible mode of operation is compared to a fixed mode of operation with constant amine regeneration. Simulation results indicate a cost reduction of 10.9% for a reference accumulated capture ratio of 91%. Robustness of the optimisation to abrupt changes in CO2 feed composition and electricity price is also investigated in simulations and results are promising. The NMPC controller uses a reduced, control-oriented model of the capture plant developed from first principle conservation laws with control volumes to discretize the model equations in space.