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In this paper, a novel method is proposed for the incorporation of data-driven machine learning techniques into process optimization. Such integration improves the computational time required for calculations during optimization and benefits the online application of advanced control algorithms. The proposed method is illustrated via the chemical absorption-based postcombustion CO2 capture process, which plays an important role in the reduction of CO2 emissions to address climate challenges. These processes simulated in a software environment are typically based on first-principle models and calculate physical properties from basic physical quantities such as mass and temperature. Employing first-principle models usually requires a long computation time, making process optimization and control challenging. To overcome this challenge, in this study, machine learning algorithms are used to simulate the postcombustion CO2 capture process. The extreme gradient boosting (XGBoost) and support vector regression (SVR) algorithms are employed to build models for prediction of carbon capture rate (CR) and specific reboiler duty (SRD). The R2 (a statistical measure that represents the fitness) of these models is, on average, greater than 90% for all the cases. XGBoost and SVR take 0.022 and 0.317 s, respectively, to predict CR and SRD of 1318 cases, whereas the first-principal process simulation model needs 3.15 s to calculate one case. The models built by XGBoost are employed in the optimization methods, such as an agent-based approach represented by the particle swarm optimization and stochastic technique indicated by the simulated annealing, to find specific optimal operating conditions. The most economical case, in which the CR is 72.2% and SRD is 4.3 MJ/kg, is obtained during optimization. The results show that computations with the data-driven models incorporated in the optimization technique are faster than first-principle modeling approaches. Thus, the application of machine learning techniques in the optimization of carbon capture technologies is demonstrated successfully. [ABSTRACT FROM AUTHOR]

Axial turbines are the most common turbine configuration for electric power generation and propulsion systems due to their versatility in terms of power capacity and range of operating conditions. Mean-line models are essential for the preliminary design of axial turbines and, despite being covered to some extent in turbomachinery textbooks, only some scientific publications present a comprehensive formulation of the preliminary design problem. In this context, a mean-line model and optimization methodology for the preliminary design of axial turbines with any number of stages is proposed. The model is formulated to use arbitrary equations of state and empirical loss models and it accounts for the influence of the diffuser on turbine performance using a one-dimensional flow model. The mathematical problem was formulated as a constrained, optimization problem, and solved using gradient-based algorithms. In addition, the model was validated against two test cases from the literature and it was found that the deviation between experimental data and model prediction in terms of mass flow rate and power output was less than 1.2% for both cases and that the deviation of the total-to-static efficiency was within the uncertainty of the empirical loss models. Moreover, the optimization methodology was applied to a case study from the literature and a sensitivity analysis was performed to investigate the influence of several variables on turbine performance, concluding that: (1) the minimum hub-to-tip ratio constraint is always active at the outlet of the last rotor and that its value should be selected as a trade-off of aerodynamic performance and mechanical integrity; (2) that the total-to-static isentropic efficiency of turbines without diffuser deteriorates rapidly when the pressure ratio is increased; and (3) that there exist a loci of maximum efficiency in the specific speed and specific diameter plane (Baljé diagram) that can be predicted with a simple analytical expression. [ABSTRACT FROM AUTHOR]

Annular diffusers are frequently used in turbomachinery applications to recover the discharge kinetic energy and increase the total-to-static isentropic efficiency. Despite its strong influence on turbomachinery performance, the diffuser is often neglected during the preliminary design. In this context, a one-dimensional flow model for annular diffusers that accounts for the impact of this component on turbomachinery performance was developed. The model allows use of arbitrary equations of state and to account for the effects of area change, heat transfer, and friction. The mathematical problem is formulated as an implicit system of ordinary differential equations that can be solved when the Mach number in the meridional direction is different than one. The model was verified against a reference case to assess that: (1) the stagnation enthalpy is conserved and (2) the entropy computation is consistent and it was found that the error of the numerical solution was always smaller than the prescribed integration tolerance. In addition, the model was validated against experimental data from the literature, finding that deviation between the predicted and measured pressure recovery coefficients was less than 2% when the best-fit skin friction coefficient is used. Finally, a sensitivity analysis was performed to investigate the influence of several input parameters on diffuser performance, concluding that: (1) the area ratio is not a suitable optimization variable because the pressure recovery coefficient increases asymptotically when this variable tends to infinity, (2) the diffuser should be designed with a positive mean wall cant angle to recover the tangential fraction of kinetic energy, (3) the mean wall cant angle is a critical design variable when the maximum axial length of the diffuser is constrained, and (4) the performance of the diffuser declines when the outlet hub-to-tip ratio of axial turbomachines is increased because the channel height is reduced. [ABSTRACT FROM AUTHOR]

This article covers the use of supplementary firing in a gas-combined cycle power plant when high flexibility is required depending on the penetration of variable renewable energies and under different gas turbine loads. Process models were simulated under different operating conditions with the software EBSILON®Professional. Five main conditions were studied for the designed combined cycle: gas turbine part-load without supplementary firing, gas turbine full load with supplementary firing, the use of supplementary firing to overcome the effect of changing ambient conditions, part-load gas turbine performance with supplementary firing technology and the use of supplementary firing in case of gas turbine shutdown. [ABSTRACT FROM AUTHOR]

This paper presents a set of steady-state and transient data for dynamic process model validation of the chemical absorption process with monoethanolamine (MEA) for post-combustion CO2 capture of exhaust gas from a natural gas-fired power plant. The data selection includes a wide range of steady-state operating conditions and transient tests. A dynamic process model developed in the open physical modeling language Modelica is validated. The model is utilized to evaluate the open-loop transient performance at different loads of the plant, showing that pilot plant main process variables respond more slowly at lower operating loads of the plant, to step changes in main process inputs and disturbances. The performance of four decentralized control structures is evaluated, for fast load change transient events. Manipulation of reboiler duty to control CO2 capture ratio at the absorber's inlet and rich solvent flow rate to control the stripper bottom solvent temperature showed the best performance. [ABSTRACT FROM AUTHOR]

The utilization of combined cycles for offshore cogeneration of power and heat is an attractive option to reduce the CO2 emissions directly related to the oil and gas sector. Main challenges for their efficient implementation are the potentially large heat-to-power ratios and the variability of power and heat requirements throughout the different stages of a field's lifetime. This paper aimed to provide the first elements for an assessment of the technology. Two combined cycle configurations were evaluated (backpressure and extraction steam turbine cycle), as well as different scenarios of power and heat requirements. The optimum design approach was firstly investigated. Designing the combined cycle at the end-life conditions, rather than at peak conditions, demonstrated to return better overall performance, when the entire plant's lifetime is considered. A comparative analysis between the defined optimum designs was then carried out. Although the backpressure steam turbine cycle demonstrated to be feasible in all the cases analyzed, it showed to be effective only for offshore installations characterized by low temperature large process heat demands. On the other hand, the extraction steam turbine cycle could not meet large process heat demands but it was very attractive when the heat requirements were more limited, irrespective of the temperature at which this heat was requested. [ABSTRACT FROM AUTHOR]

Implementation of energy efficient technologies is an issue of growing importance for the offshore oil and gas industry. Rising awareness of increasing levels of CO2in the atmosphere is a major driver in this move, with a main aim being to reduce the amount of released CO2 per unit of oil or natural gas produced. Subsequently, the addition of steam bottoming cycles to exploit exhaust heat from gas turbines offshore has become an attractive alternative. This paper will investigate two different combined cycle configurations, namely the extraction steam turbine- and the backpressure steam turbine-cycle. Both cycles were modelled using the process simulation software Ebsilon Professional with a single GE LM2500+G4 gas turbine as a topping cycle, and a once-through heat recovery steam generator to exploit GT exhaust heat. At design, the steam turbines produced 8.2 MW and 6.0 MW respectively, achieving net thermal efficiency of 45.5%/42.1%. This was a 12.3 pp/8.9 pp increase compared to the simple cycle GE LM2500+G4 configuration. The findings suggest that a backpressure steam turbine could be an attractive option for oil producing facilities with high demand for process heat, while an extraction steam turbine configuration is more suited to gas producing facilities with lower heat requirements and a higher demand for power and flexibility. Additionally, both cycles displayed a substantial reduction in emitted CO2 per MWh produced, with reductions 26% and 21% compared to the simple cycle configuration achieved for the extraction and backpressure cycle respectively. [ABSTRACT FROM AUTHOR]

Since the development of the first oil fields on the Norwegian Continental Shelf, the petroleum industry in Norway has been making continuous progress in oil production engineering. With greater environmental awareness and increasing taxation of NOx and CO2 emissions, the economic pressure has been rising in recent decades. The energy demand for offshore oil and gas production is high. With a view to improving power generation on offshore oil and gas installations, four models of di erent power cycles were investigated: a simple cycle gas turbine (currently the default option), a compact combined cycle with enhanced fuel utilization, a steam injection gas turbine cycle as an innovative solution, and a state of the art combined cycle for onshore applications as a reference cycle. Special requirements for offshore installations are discussed and sizing was identified as the major criterion. The power demand of an oil platform and its change during di erent states in field life were analyzed. To complete the simulations, the models were set to off-design conditions and the part-load behavior was investigated. The plant layouts were laid out and visualized with 3D CAD models. [ABSTRACT FROM AUTHOR]

This paper addresses the challenges and possibilities related to offshore steam bottoming cycles with a special focus on once-through heat recovery steam generators (HRSGs). The main focus of the paper is to investigate the compromise between weight and efficiency of the HRSG by process simulation. The cost per installed kg of equipment is high offshore. Therefore, any bottoming cycle, applied to the back-end of the gas turbine, needs to be compact, yet sufficiently efficient. Important parameters to make the HRSG compact were the number of steam pressure levels, the HRSG technology, the flue gas pressure drop in the HRSG, and the pinch-point temperature difference. While selecting the parameters as a compromise between weight and efficiency, the combined cycle net plant efficiency was found to be approximately 50% with a power output of 43 MW. The steam turbine gross power output was 11 MW or about 25% of the total combined cycle plant gross power output. These results were compared to an onshore reference plant model which utilized the same type of aeroderivative gas turbine. The weight of the offshore once-through HRSG was about one third of the onshore HRSG. The net plant efficiency was 3%-points lower for the offshore system. [ABSTRACT FROM AUTHOR]

Abstract: Most energy scenarios suggest carbon capture and storage (CCS) from power generation might contribute to reduce the carbon emissions necessary to stabilize the long-term global average atmospheric temperature. GE is actively investigating and developing novel technologies for both capturing and compressing CO2 from power plants with potential lower energy requirements and environmental impact than state-of-the-art processes. One technology that is currently the focus of significant research effort is phase-changing absorbents for post-combustion capture applications. This investigation compared the performance of phase-changing absorbents to state-of-the-art monoethanolamine (MEA) capture for three different flue gas conditions with CO2 concentrations ranging from 4 mole% to 13 mole%. Results indicate that depending on the flue gas conditions, the specific equivalent work necessary for operating phase-changing absorbents is expected to be up to 40% lower than for MEA capture. However, as the level of maturity of phase-changing absorbents is certainly lower than MEA capture, higher uncertainty in performance is expected. Besides lower energy requirements, a reduction of up to 6% in specific water cooling load is expected from the phase-changing absorbents compared to MEA capture, in particular for cases with high CO2 concentrations in the flue gas. [Copyright &y& Elsevier]

Abstract: One option for pre-combustion CO2 capture in power plants is the integrated reforming combined cycle (IRCC). IRCCs have previously been studied from multiple viewpoints: thermo-economic analysis, process optimization, environmental impact, and plant flexibility. This paper is focused on the design of the heat recovery steam cycle (HRSC), including the heat recovery steam generator (HRSG), and aims to define the optimal steam cycle configurations for plant efficiency and dual-fuel flexibility. A recently developed optimization algorithm was successfully applied to obtain a set of flexible and efficient designs for IRCCs. Results showed that the preferred designs consisted of a dual-pressure level HRSG with reheat and limited supplementary firing in duct burners, high-pressure evaporators and economizers in the syngas coolers, limited high-pressure level (140–154bar), and feedwater preheating. The most attractive optimized dual-pressure designs showed improvements of approximately 0.5% points in the net plant efficiency compared to the non-optimized base case. The resulting net plant efficiency was about 45.8% with a net power output of around 425MW for the best cases. [Copyright &y& Elsevier]