Carbon capture from natural gas combined cycle power plants: Solvent performance comparison at an industrial scale

Natural gas is an important source of energy. This article addresses the problem of integrating an existing natural gas combined cycle (NGCC) power plant with a carbon capture process using various solvents. The power plant and capture process have mutual interactions in terms of the flue gas flow rate and composition vs. the extracted steam required for solvent regeneration. Therefore, evaluating solvent performance at a single (nominal) operating point is not indicative and solvent performance should be considered subject to the overall process operability and over a wide range of operating conditions. In the present research, a novel optimization framework was developed in which design and operation of the capture process are optimized simultaneously and their interactions with the upstream power plant are fully captured. The developed framework was applied for solvent comparison which demonstrated that GCCmax, a newly developed solvent, features superior performances compared to the monoethanolamine baseline solvent

MANAGEMENT DECISION SUPPORT SYSTEM OF SOLVENT-BASED POST-COMBUSTION CARBON CAPTURE

A management decision-support framework for a coal-fired power plant with solvent based post combustion CO2 capture (PCC) (integrated plant) is proposed and developed in this thesis. A brief introduction pertaining to the solvent-based PCC technology, thesis motivations and objectives are given in Chapter 1. Chapter 2 comprises a comprehensive literature review of solvent-based PCC plant from the bottom level (PCC instrumentation level) until the top level (managerial decision of PCC system). Chapter 3 describes the development of solvent-based PCC dynamic model via empirical methods. Open-loop dynamic analyses are presented to provide a deeper understanding of the dynamic behaviour of key variables in solvent-based PCC plant. Chapter 4 presents the design of the control architecture for solvent-based PCC plant. Two control algorithms developed, which utilise conventional proportional, integral and derivative (PID) controller and advanced model predictive control (MPC). Chapter 5 proposes a conceptual framework for optimal operation of the integrated plant. The MPC scheme is chosen as the control algorithm while mixed integer non-linear programming (MINLP) using genetic algorithm (GA) function is employed in the optimization algorithm. Both algorithms are integrated to produce a hybrid MPC-MINLP algorithm. Capability and applicability of the algorithm is evaluated based on 24 hours and annual operation of integrated plant. Chapter 6 extends the scope of Chapter 5 by evaluating the relevance of solvent-based PCC technology in the operation of black coal-fired power plant in Australia. This chapter considers a prevailing climate policy established in Australia namely Emission Reduction Fund (ERF). Finally, the concluding remarks and future extensions of this research are presented in Chapter 7

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

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

Analysis and control co-design optimization of natural gas power plants with carbon capture and thermal energy storage

2022 Summer.Includes bibliographical references.In this work, an optimization model was constructed to help address important design and operation questions for a novel system combining natural gas power plants (NGCC) with carbon capture (CC) and hot and cold thermal energy storage (TES) units. The conceptualization of this system is motivated by the expected evolution of the electricity markets towards a carbon-neutral electricity grid heavily penetrated by renewable energy sources, resulting in highly variable electricity prices and demand. In this context, there will be an opportunity for clean, flexible, and cheap fossil fuel-based generators, such as NGCC plants with CC, to complement renewable generation. However, while recent work has demonstrated that high CO2 rates are achievable, challenges due to high capital costs, flexibility limitations, and the parasitic load imposed by CC systems onto NGCC power plants have so far prevented its commercialization. Coupling TES units with CC and NGCC would allow to store thermal energy into the TES units when the electricity prices are low, either by subtracting it from the NGCC or by extracting it from the grid, and to discharge thermal power at peak prices, from the hot storage (HS) to offset the parasitic load of the CC system and from the cold storage (CS) for chilling the inlet of the NGCC combustion turbine and increase the output of the cycle beyond nominal value. For the early-stage engineering studies investigating the feasibility of this novel system, a control co-design (CCD) approach is taken where key plant sizing decisions (including storage capacities and energy transfer rates) and operational control (e.g., when to store and use thermal energy and operate the power plant) are considered in an integrated manner using a simultaneous CCD strategy. The optimal design, as well as the operation of the system, are determined for an entire year (either all-at-once or through a moving prediction horizons strategy) in a large, sparse linear optimization problem. The results demonstrate both the need for optimal operation to enable a fair economic assessment of the proposed system as well as optimal sizing decisions due to sensitivity to a variety of scenarios, including different market conditions, site locations, and technology options. After detailed analysis, the technology shows remarkable promise in that it outperforms NGCC power plants with state-of-the-art CC systems in many of the scenarios evaluated. The best overall TES technology solution relies on cheap excess grid electricity from renewable sources to charge the TES units -- the HS via resistive heating and the CS through an ammonia-based vapor compression cycle. Future enhancements to the optimization model are also discussed, which include additional degrees of freedom to the CC system, adapting the model to evaluate other energy sources and storage technologies, and considering uncertainty in the market signals directly in the optimization model

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

Combined heat and power plants in decarbonized energy systems: Techno-economics of carbon capture and flexibility services at the plant, city and regional levels

Our present energy system is the main driver of climate change. Variable renewable electricity generation and carbon dioxide removal (CDR) are key technologies in the transformation to a sustainable energy system, but their broad implementation implies challenges related to energy system flexibility and energy requirements of CDR technologies. The aim of this thesis is to investigate the potential and incentives for combined heat and power (CHP) plants in Sweden to contribute with CDR and flexibility services in the energy system. A techno-economic assessment scheme that considers variability in boundary conditions, such as electricity prices, and includes the CHP plant, city, and regional energy system levels is developed and applied. System optimization modeling and process-level case studies are performed to investigate how CHP plant flexibility measures are utilized and valued, and to estimate the cost and potential of CDR from Swedish CHP plants.The results indicate a large potential for Swedish CHP plants to contribute to CDR, with at least 10 MtCO2/year being available for capture and storage. The realizability of this potential is challenged by the cost of carbon capture which increases notably for CHP plants that are small and have few full load hours. CHP plants can cost-effectively contribute with flexibility provision in the studied electricity system, although the impact on the total system is limited, as the installed capacity of CHP plants is small relative to the magnitude of net load variability. From a plant perspective, the plant revenue can increase if the operation is scheduled to follow electricity price variability, but this requires a significant level of price volatility and access to large-scale thermal energy storage for maximum benefit. The fuel price has a strong impact on the competitiveness of biomass-fired CHP plants on a regional level, that compete with power-to-heat technologies in the district heating sector. In contrast, in cities, there are stronger incentives for CHP plants as heat producers regardless of how the surrounding energy system and market prices develop, due to a limited availability of other technology options and a limited grid connection capacity to drive power-to-heat

Investigation of control strategies for adsorption-based CO2 capture from a thermal power plant under variable load operation

This work considers the closed-loop behavior of a moving bed temperature swing adsorption process designed to capture CO2 from a coal-fired power plant. Four decentralized control strategies were studied based on step changes and ramps of flue gas feed flow rate and controller setpoint changes. A proportional-integral (PI) control configuration, where CO2 purity was controlled by hot fluid velocity to the desorption section and CO2 recovery was controlled by the sorbent flow rate, demonstrated the overall best performance. The 99% settling time for higher-level control variables varied from 0 to 13 min for most control configurations and the settling time for CO2 purity was generally longer than for CO2 recovery. The simulations show that using ratio controllers lead to larger offsets but can give around 10 times faster purity response compared to PI-control. All investigated control combinations were able to keep the controlled variables relatively close to the setpoints and the largest relative steady state setpoint offset was 2%.publishedVersio

Optimal Design and Operation of Integrated Hydrogen Generation and Utilization Plants

There are considerable efforts worldwide for reducing the use of fossil fuel for energy production. While renewable energy sources are being increasingly used, fossil fuel still contribute about 80% of the energy used worldwide. As a result, the level of CO2 is still increasing fast in the atmosphere currently exceeding about 410 parts per million (ppm). For reducing CO2 build up in the atmosphere, various approaches are being investigated. For the electric power generation sector, two key approaches are post-combustion CO2 capture and use of hydrogen as a fuel for power generation. These two solutions can also be integrated together in a flexible power plant configuration. This research presents two novel energy systems where hydrogen is being utilized in a power plant for the co-firing of natural gas. The first system is NGCC power plant integrated with a post combustion carbon capture technology and hydrogen production unit. The second system is a standalone Peaker plant (simple cycle plant) integrated with hydrogen production unit. The techno-economic analysis of these two systems will enable us to understand the optimal design and operational performance of this energy systems. The Net Present Value (NPV) optimization was used for the techno-economic analysis of the two energy systems at different conditions. Different tax scenario was also investigated for the electricity price (LMP) used in the optimization scheme. As part of development of optimization work, reduced order models (ROM) were developed for the more sophisticated and nonlinear models of the standalone models. A clustering algorithm with a derivative consideration was also developed to reduce the number of optimization days needed for a year-long optimization. For these two-hydrogen utilization configuration, the optimal design conditions of the hydrogen production unit were decided, and it was shown that these optimal values change with the electricity market profiles

Solvent-based post-combustion CO2 capture for power plants: A critical review and perspective on dynamic modelling, system identification, process control and flexible operation

Solvent-based post-combustion CO2 capture (PCC) appears to be the most effective choice to overcome the CO2 emission issue of fossil fuel fired power plants. To make the PCC better suited for power plants, growing interest has been directed to the flexible operation of PCC in the past ten years. The flexible operation requires the PCC system to adapt to the strong flue gas flow rate change and to adjust the carbon capture level rapidly in wide operating range. In-depth study of the dynamic characteristics of the PCC process and developing a suitable control approach are the keys to meet this challenge. This paper provides a critical review for the dynamic research of the solvent–based PCC process including first-principle modelling, data-driven system/process identification and the control design studies, with their main features being listed and discussed. The existent studies have been classified according to the approaches used and their advantages and limitations have been summarized. Potential future research opportunities for the flexible operation of solvent-based PCC are also given in this review