Supercritical Power Research Articles

Co-firing characteristic prediction of solid waste and coal for supercritical CO2 power cycle based on CFD simulation and machine learning algorithm

The co-firing technology of combustible solid waste (CSW) and coal in the supercritical CO2 (S-CO2) circulating fluidized bed (CFB) can effectively deal with domestic waste, promote social and environmental benefits, improve the coal conversion rate, and reduce pollutant emission. This study focuses on the co-firing characteristics of CSW and coal under S-CO2 power cycle, and simulations are conducted by employing Multiphase Particle-in-cell (MP-PIC) method integrated with the comprehensive chemical reaction models in a 300 MW S-CO2 CFB boiler. Effects of operating parameters including fuel mixture proportion and first stage stoichiometry on the gas emission characteristics are further analyzed. Based on training and testing database based on the simulation results, a novel Improved Whale Optimization Algorithm and Bi-dictionary Long Short-Term Memory (IWOA-BiLSTM) algorithm model is established to predict CFB temperature, NOx emission concentration, and SO2 emission concentration, respectively. Results show that CO and SO2 decrease with the coal mass ratio of the fuel mixture increasing, while NOx increases. With the increase of first stage stoichiometry, CO increases, NOx declines, and the change of SO2 is not obvious. Compared with two other basic algorithm models, the prediction error of the proposed algorithm model for the three targets is minimal with the average relative error of 0.032 %, 0.231 %, and 0.157 %, respectively, which can meet the prediction requirements with acceptable accuracy.

A real-time phase transition modeling of supercritical steam cycle and load variation rate enhancement of thermal power plants under deep peak shaving

The ambitious green revolution to renewable energy sources in global power grids necessitates massive integration of solar and wind energy, which involves intermittent and unpredictable challenges. Thermal power plants are crucial in stabilizing the grid and addressing these challenges through flexibility reformation including deep peak shaving and frequent load variations since the unsteady state energy transfer and thermal dynamics during combustion and heat transformation in thermodynamic processes vary significantly. These conditions lead to issues such as furnace instability and latent heat of phase transition. This study introduces a novel approach to modeling phase transitions of supercritical steam cycle, and investigatesthe length, position, temperature, and energy transfer of the working medium and components under normal and low operational states. Conducting and analyzing the thermal feasible region associating the security of components and working medium this study establishes a control strategy for dynamic heat transfer to reduce component degradation effects andenhance load variation rate under flexible operations. Simulation model of a supercritical power unit based on the proposed method demonstrates an accuracy of 97.94%. Results from the optimal approach in maximizing load variation rate show the effectiveness and achieve 1.2%p.e./min most under transition process.

Perspectives on oxy-fuel combustion for supercritical CO2 direct-fired power cycle

This paper explores the potential of oxy-fuel direct-fired supercritical carbon dioxide (sCO2) power cycles, proposing them as a promising strategy towards achieving near-total carbon capture while utilizing existing fossil fuels. It offers insights into the future of CO2- and sCO2-diluted combustion science and combustor design, supported by a review of the current state of the art. The paper is divided into four sections: chemical kinetics and the development of chemical mechanisms, numerical simulations tools, combustion and laser ignition experimental efforts, and the current state of the art and perspectives of combustor design efforts. The paper underscores the need for additional experimental measurements to validate chemical mechanisms, numerical simulations, and combustor design to advance understanding of CO2 and sCO2-diluted combustion science. The authors advocate for increased collaboration within the scientific community and the development of standardized lab-scale burners and combustor geometries to facilitate comparison and validation as well as reduce development costs. The paper emphasizes that significant research and development efforts are crucial to ensuring the safety, reliability, and efficiency of CO2 and sCO2-diluted combustion processes and combustor design. The knowledge and strategies applicable to conventional gas turbines may not directly transfer to sCO2 cycles, necessitating dedicated research efforts to advance this promising technology towards widespread adoption.

Techno-economic analysis and optimisation of Piperazine-based Post-combustion carbon capture and CO2 compression process for large-scale biomass-fired power plants through simulation

This study aims to investigate a cost-effective and energy-efficient amine-based post-combustion carbon capture (PCC) process for large-scale supercritical biomass-fired power plants (SC BFPP). Thus, we have quantified the energy and economic performance of the PCC process with different configurations and solvents. Three process configurations which included the standard configuration, the absorber intercooler (AIC) with the advanced flash stripper (AFS) and the AIC, AFS and side stream extraction (SSE) were simulated in Aspen Plus® V11 using 30 wt% and 40 wt% piperazine (PZ) as solvent. In addition to this, CO2 compression trains using the heat pump (HP) and supercritical CO2 cycle (s-CO2) were also simulated. Sensitivity analysis of the PCC process was carried out to investigate the impact of important parameters on the energy performance of the process. Furthermore, energy analysis shows that a minimum energy consumption of 2.78 GJ/tCO2 was achieved with the PCC process using 40 wt% PZ, a combination of the AIC, AFS and SSE for capture and s-CO2 for compression. This achieved a significant energy saving of 1.01 GJ/tCO2 compared with the standard PCC process using 30 wt% monoethanolamine that is used as the benchmark in this study. The economic analysis results showed that the minimum CO2 capture cost of 55.70 $/tCO2 was achieved using the AIC-AFS-SSE-sCO2 configuration and 40 wt% PZ as solvent. This represents a 19.5 % reduction in cost compared with the standard 40 wt% PZ process with a cost of 69.18 $/tCO2. The optimisation of the PZ-based PCC process was carried out to determine the optimal solvent concentration with the minimum carbon capture cost. It was found that the optimal PZ concentration for the PCC process based on standard and AFS configurations were 37.5 wt% and 32.5 wt%, respectively. The optimisation of the stripper pressure for the minimum carbon capture cost was conducted. As a result, compared with the standard PCC process using 40 wt% PZ, the energy consumption and CO2 capture cost of the optimised process at the suggested pressure of 7 bar were reduced by 41.6 % and 32.4 %, respectively.

Thermodynamic analysis of supercritical CO2 power generation system for waste heat recovery with impurities in CO2

Waste heat recovery from gas turbines is an effective method for meeting the demand for a more efficient and cleaner energy system with decreased CO2 emissions and lower environmental pollution. The supercritical CO2 Brayton cycle is a promising power conversion system for waste heat recovery. The advantage of the supercritical CO2 Brayton cycle can be attained based on its physical characteristics. However, when another fluid is mixed as an impurity in a system using pure CO2, physical characteristics of working fluid was changed and operation at the design point can be challenging. Therefore, it is important to verify the purity of CO2 and understand the effect of impurities in CO2 in advance. This study examined the effects of impurities in the working fluid of a supercritical CO2 power generation system for actual demonstration facilities. The effect of impurity, a CO2-based mixture, in a supercritical CO2 power generation system on waste heat recovery from an LM500 gas turbine was investigated. A purity test of industrial grade CO2, which was noted as 99.9 % pure by the supplier, was conducted to verify the composition of the working fluid. The results of the purity test showed that the supplied CO2 consisted of 99.076 % CO2 along with nitrogen, argon, oxygen, water, and methane. Based on the results of the purity test, sensitivity analyses of the CO2-based binary mixtures and industrial mixtures were performed. A design point analysis was conducted for the CO2-based industrial mixture in comparison with pure CO2, which has cycle efficiency of 16.15 %, gross power of 510.03 kW, mass flow rate of 12.55 kg/s, and waste heat recovery of 2119.06 kW. In the case of fixed waste heat with mass flow rate of 14.417 kg/s, the cycle efficiency decreased by 0.39 % and gross power increased by 66.14 kW. In the case of fixed mass flow rate with 1844.598 kW waste heat, the cycle efficiency decreased by 0.32 % and gross power decreased by 9.84 kW. In addition, the influence of the performance of the major components on the system performance was investigated.

Investigating the impact of nanofluids and exergy metrics for integrated solar-biomass SCO2 power and desalination cycles

Several strategies have emerged for utilizing waste heat across diverse sectors. Yet, integrated systems that merge power generation with freshwater production, especially those leveraging renewable energy, remain relatively unexplored. Addressing this gap, a novel solar biomass-driven system is under development for power generation and desalination facilities. In the suggested system, rather than wasting the energy of a supercritical CO2 power cycle, a bottoming cycle is proposed to augment energy utilization factor (EUF). By integrating humidification-dehumidification, thermal vapor compression, and reverse osmosis (HDH-TVC-RO) with a multi-effect distillation (MED) unit, freshwater production rate is significantly enhanced. The outcomes reveal a freshwater output of 29.36 kg/s, a gained output ratio (GOR) of 17.36, and the EUF of 3.372. Various nanofluids have been assessed for the solar collector and due to superior total exergy efficiency and less corrosion effects, Cu- and carbon-based nanoparticles are recommended. Sensitivity analysis indicates that increasing the pressure ratio of compressors boosts the total GOR. Furthermore, adjustments to both the parameters of pressure of steam fed to HDH-TVC, and the compressor pressure ratio demonstrate a linear effect on EUF behaviour.

Comprehensive analysis and thermo-economic optimization of the dry cooling system for supercritical CO2 power cycle

This paper presents a comprehensive analysis and optimization of the dry cooling system for the supercritical CO2 (sCO2) power cycle, a promising technology for generating electricity from renewable heat sources. Unlike prior studies that concentrated solely on specific cooling system components, this paper examines thermoeconomic factors and employs mathematical models to analyze how various operational parameters impact both the cooling system's performance and cost, as well as the overall power cycle. Additionally, the paper employs a multi-objective optimization method to determine the optimal parameter values across varying cooling capacities and ambient temperatures. The results show that the thermal efficiency of the power cycle does not increase linearly with the cooling capacity, due to the change in CO2's physical properties near the temperature and pressure where it behaves like both a liquid and a gas (the pseudo-critical point). Furthermore, optimal cooling system area varies based on cooling capacity and ambient temperature, leading to cost reduction and improved power system efficiency. This paper provides a useful tool and guidance for designing and operating the dry cooling system for the sCO2 power cycle.

Environmental, technological, and economic analysis of supercritical coal-fired power system.

Developing countries primarily rely on fossil-based energy sources to meet their energy demands. The use of fossil fuels has several adverse environmental repercussions that damage the biosphere both directly and indirectly. Among fossil fuels, coal brings about the heaviest environmental externalities, yet its abundance makes its use widespread, particular in countries having significant power generation deficits, such as Pakistan. This study presents an environmental, technological, and economic analysis of a supercritical coal-based power unit located in Pakistan and used for electricity generation. For environmental assessment, the CML-1A baseline method in OpenLCA software was used, and eight midpoint impact indicators were selected. The functional unit chosen was 1 MWh of generated electricity. The results indicated that the category of ozone layer depletion has the least impact, whereas global warming potential has the highest impact score. Except for photochemical oxidation and human toxicity, the plant operational stage dominated most of the selected impact categories. The current paper also reveals that the removal efficiency of CO2 and other pollutants is higher in supercritical compared to subcritical plants. Moreover, the economic feasibility of supercritical plant is compared with chemical looping combustion (CLC)-based supercritical coal-fired power plant, and results shows that CLC-based coal-fired power plant is a more competitive and environmentally friendly option. The utilization of a scientific cleaner energy-management system in real-time, as exemplified in this study, may facilitate the development of a optimalpolicy framework that encouragesfor the adoption of cleaner coal power generation in developing countries, ultimately resulting in improved energy sustainability. Furthermore, this paper also presents some policy implications which could be helpful for policymakers, researchers, and industrialists to improve the sustainability of energy in emerging economies.

Accuracy assessment of the turbomachinery performance maps correction models used in dynamic characteristics of supercritical CO2 Brayton power cycle

The supercritical CO2 Brayton cycle (SCO2BC) has emerged as a promising next-generation power generation technology due to its potential for high thermal efficiency and compact components design. Dynamic modeling of SCO2BC is crucial for understanding and analyzing its performance under design and off-design conditions. Turbomachines are critical components in SCO2BC dynamic models. While turbomachinery components are often modeled using their design-point turbomachinery performance maps (TPM), these maps become less accurate during off-design operations. Despite the existence of various TPM correction methods that ensure model validity, the implementation of the accurate ones within dynamic SCO2BC models remains scarce in the literature. This is crucial as it potentially compromises the accuracy of the obtained results. Therefore, there is a need to investigate the errors in the existing literature TPM correction models (in dynamic SCO2BC simulation) by comparing them against dynamic SCO2BC models employing a highly accurate correction method. Thus, in the current work, the common TPM correction methods from the literature are implemented in SCO2BC dynamic models and compared against a baseline mode, which uses the highly-accurate Pham method (at both the component and cycle levels). To the authors’ knowledge, this is the first work to address this research gap for the SCO2BC dynamic simulations and on both component and cycle levels. Additionally, another novelty is the usage of Simcenter Amesim software to dynamically model the SCO2BC aided with Pham model. Multible dynamic models for both the turbomachines of SCO2BC and the whole cycle are constructed and equipped with the different TPM correction methods found in literature to compare their dynamic behaviour that of Pham model. The Ideal Gas Compressibility factor (IGZ) method demonstrates a better performance than the other tested methods, as it exhibits the lowest discrepancy compared to the Pham model. Many of the other tested methods show significant errors. Furthermore, a popular hybrid correction combining IGZ and Pham (IGZ-Ph) is also investigated. Surprisingly, while seemingly beneficial, this hybrid approach negatively impacts accuracy, even resulting in predictions as if no correction was applied.

Thermodynamic analysis of the air separation unit and CO2 purification unit in the semi-closed supercritical CO2 cycle with nearly zero emission

The natural gas-fired semi-closed supercritical CO2 cycle is an efficient oxyfuel combustion power generation technology featuring nearly zero emissions. This study investigated the interaction of the semi-closed supercritical CO2 power unit with the air separation unit (ASU), which supplies O2 for combustion and adiabatic compression heat for the heat recovery process in the power unit, and the CO2 purification unit (CPU), which refines the CO2 in the exhaust gas to 99.97% for enhanced oil recovery (EOR) applications. The detailed thermodynamic models of the power unit, ASU, and CPU have been constructed to explore the impact of variations in oxygen purity and excess oxygen coefficient on the overall thermodynamic performance of the system. The results demonstrate that the net electric efficiency peaks at an oxygen purity of 98%, and a one percent decrease in oxygen purity reduces the net electrical efficiency by approximately 0.36% to 0.97% points. Moreover, the net electric efficiency decreased by 0.10% points when the excess oxygen coefficient increased from 3.00% to 13.67%. These findings may offer valuable guidance for developing oxyfuel combustion power generation technologies.

Performance and optimization evaluation for integration of sCO2 power system into the aircraft propulsion system

The aviation industry accounts for part of the CO2 emissions contributing to climate change. The industry has established a target to reduce 2050 net aviation carbon emissions by 50 % relative to 2005 levels. With this in mind, waste heat recovery is a key pathway to achieve reduced emissions and improve system efficiency. The waste heat may potentially be converted to electric power using a supercritical CO2 Brayton power cycle. The sCO2 power system offers the advantage of compactness owing to the high working fluid density, which is an important consideration for aircraft performance. The present work focuses on the integration of the sCO2 power system into the aircraft propulsion system and evaluation of its performance. Detailed optimization of the sCO2 waste heat system will be evaluated with a focus on cycle efficiency and net power under different operating conditions, including ground, takeoff, climb, cruise, and landing operations. The study is divided into two parts with two different turbofan engines, one with a nominal thrust of 30 kN and the other with a nominal thrust of 9 kN. The first part shows the effect and operation of the waste heat recovery unit under the different operating conditions. The second part is focused on cycle optimization and performance evaluation. The results demonstrate the potential of waste heat recovery during a range of operational conditions. The sCO2 cycle efficiency can reach between 25 and 39 % (depending on aircraft engine) with net power output in the range of 100 to 260 kW.

Modeling of Metal Matrix Concentrated Solar Receivers for sCO2 Power Blocks

Abstract Supercritical CO2 power blocks for Concentrating Solar Power (CSP) with novel metal matrix solar receivers have the potential to reduce operating expenses while improving overall system efficiencies. These concentrated solar receivers integrated with a metal matrix-based phase change (PCM) thermal storage medium provide the compounding effect of an efficient heat exchanger while also integrating thermal storage within the receiver. Detailed numerical modeling of such devices with enthalpy-porosity-based formulation for phase change and turbulent convective heat transfer for the sCO2 microchannels is described in the current work. With sCO2 power blocks operating at temperatures and pressures beyond 800°C and 200 bar, different high-temperature PCMs are studied. A detailed steady charging followed by discharge and charging transients is simulated to analyze the thermal performance of these devices. In the current work, the energy storage density of PCMs is studied, followed by an analysis of the movement of the melt-pool interface over the streamwise length of a high corrugation wavy microchannel. A scaling analysis is carried out to estimate the heat transfer coefficients while compare them with the numerical model predictions. The results from the current work can be utilized for sizing and detailed design of integrated solar receivers for high-temperature sCO2 power block applications.

Dynamic modeling and model predictive control for printed-circuit heat exchanger in supercritical CO2 power cycle

The supercritical carbon dioxide (sCO2) Brayton cycle, known for its superior thermal efficiency and compact turbomachinery size, can utilize various heat sources. The printed-circuit heat exchangers (PCHE) used in the power cycle, particularly the recuperators and cooler, significantly influence the thermal efficiency of the cycle. However, they exhibit intricate characteristics attributed to large thermal inertia and nonlinear heat transfer. This paper explores the one-dimensional dynamic modeling and control issues for PCHE. The established dynamic PCHE models are verified through different scenarios. Then, a novel control strategy is proposed for fast temperature reference tracking and disturbance rejection. The composite controller includes three parts: the main control is based on the principle of model predictive control (MPC); Gaussian process (GP) regression modeling is incorporated as the feedforward; and the disturbance observer (DOB) is introduced for unexpected disturbance estimation and compensation. Compared with traditional controllers, simulations demonstrate that for reference tracking the settling time of the proposed method can be saved by more than 50%, and for disturbance rejection the recovery time can be reduced by more than 30%. The results indicate the presented strategy can ensure the safe and effective operation of the sCO2 power cycle.

Economic Assessment of Coal-Fired Power Unit Decarbonization Retrofit with High-Temperature Gas-Cooled Reactors

To mitigate global warming, phasing out coal in the global energy system orderly and rapidly is an important near-term strategy. However, the majority of coal-fired plants in China have operated for less than 15 years. Accelerated coal power plant retirements would lead to substantial asset stranding. Coal-to-nuclear (C2N) technology offers a potential solution by replacing coal boilers in existing coal-fired plants with nuclear reactors. In this study, the G4-ECONS model was used to assess the economics of repowering a 600 MW supercritical coal-fired power plant with two 272 MWe high-temperature gas-cooled reactors. The timeline for the C2N project and the additional cost of dispatching electricity from the grid during retrofitting were discussed. Results showed that the C2N total capitalized costs are 19.4% (baseline estimate, USD 5297.6/kW) and 11.1% (conservative estimate, USD 5847.2/kW) lower than the greenfield project (USD 6576.5/kW), respectively. And C2N projects need to reduce LUEC by at least 20% to become competitive. This study can inform engineering design decisions leading to more precise and cost-effective C2N projects.

Direct coupling of pressurized gas receiver to a brayton supercritical CO2 power cycle in solar thermal power plants

Three layouts of Brayton supercritical CO2 power cycles directly coupled to the receiver are proposed for Generation 3 solar power plants: conventional recompression, recompression with partial cooling, and recompression with intercooling. To achieve direct coupling, the solar heat is introduced downstream of the turbine, where CO2 pressure is lower. A higher temperature rise diminishes the receiver's dimensions, thus increasing its energy efficiency. It also lowers the average working temperature since the maximum temperature is fixed at 700 °C, thereby reducing losses. However, optical efficiency decreases as the receiver size diminishes. Both intercooling and partial cooling layouts further increase the cycle's net efficiency, which reduces the receiver's size, following similar trends observed with an increase in temperature rise. Considering all these effects, various factors push in opposite directions, affecting overall efficiency and costs. This competitive interplay results in overall efficiencies ranging from 30.26 % to 31.58 % and Levelized Costs of Electricity (LCOEs) between 162.47 €/MWh and 166.81 €/MWh. In conclusion, similar outcomes in terms of energy and economics are achieved with the three layouts, suggesting the simplest layout (recompression) as the most advisable. If thermal storage is incorporated, partial cooling becomes preferable due to its significant increase in the receiver's temperature rise.

A dynamic hybrid model of supercritical once-through boiler-turbine unit including recirculation mode and once-through mode

Supercritical once-through boiler-turbine units play a paramount role in maintaining grid stability owing to their exceptional efficiency and flexibility. Nevertheless, achieving precise modeling of this device under various operational conditions remains a significant challenge. This study conducts modeling and simulation of an actual supercritical once-through coal-fired power plant. The findings signify that the hybrid model proposed herein adeptly encompasses all operational modes of supercritical once-through units, including start-up recirculation mode and once-through mode. To bolster model precision, an optimization algorithm grounded on weighted mean of vectors (INFO) has been employed for parameter identification, while the INFO-XGBoost was utilized to fashion a machine learning model for static parameters. It has been validated that the developed model accurately captures the dynamic characteristics of the unit. Furthermore, the utilization of the INFO-XGboost to model static parameters has been proved to enable the errors in principal outputs of coordinated control system to be within 0.35 % of MAPE across the entire operational process, thus facilitating the design of more refined and intelligent control systems.

Part-load analysis and preliminary annual simulation of a constant inventory supercritical CO2 power plant for waste heat recovery in cement industry

The present work investigates the part-load performance of a MW-scale sCO2 power plant designed as waste heat recovery unit for an existing cement plant located in Czech Republic, in the framework of the H2020 funded project CO2OLHEAT. The study first presents the selected power plant configuration and then focuses on the evaluation of its part-load operation due to variation of flue gas mass flow rate and temperature. The range of flue gas conditions at the outlet of the upstream process is retrieved from a preliminary statistical analysis of historical trends obtained through the cement plant monitoring. The numerical model developed for this study aims at providing realistic results thanks to the adoption of turbomachinery performance maps provided by the turbomachinery manufacturer of the project. Moreover, heat exchangers have been modelled through a discretized approach which has been validated against manufacturer data, while piping inventory and pressure losses have been assessed through a preliminary sizing that considers the actual distances to be covered in the cement plant. Performance decay is estimated for the whole range of flue gas conditions, reporting the most significant power cycle parameters, and identifying the main causes of efficiency loss. The part-load analysis is carried out considering a constant CO2 inventory, in order to reduce the system complexity and capital cost and simplify plant operation. Results show that the operation entails minor variation of the compressors operative points in the whole range of operating conditions of the cement plant, avoiding the risk of anti-surge bypass activation. Moreover, the plant is able to work close to the nominal thermodynamic cycle efficiency (20.5 %–23.0 %) for most of the year and benefits from part-load operation in terms of overall performance. In the last part of the work, a preliminary techno-economic analysis of the plant is also presented to highlight the potential advantages of sCO2 technology for waste heat recovery applications. The results of the part-load performance of the plant are combined with the flue gases data obtained from the preliminary statistical analysis and the cement plant historical monitoring. An annual electricity production equal to 13′909.7 MWh is obtained, corresponding to 6560 equivalent hours and a system capacity factor of 74.9 %. The investment cost of each CO2OLHEAT plant component is estimated by means of cost correlations obtained from literature and the non-discounted payback time is computed as a function of the electricity selling price. The results show that, even considering electricity prices before 2022, the payback time of the CO2OLHEAT plant is estimated to be lower than 8 years, justifying the industrial interest in the proposed technology.

Thermodynamic analysis and optimization of the semi-closed oxy-combustion supercritical CO2 power cycle with blending hydrogen into the natural gas/syngas

The semi-closed oxy-combustion supercritical CO2 (sCO2) cycle is regarded as a promising power cycle featuring the combined advantages of high efficiency and nearly 100 % CO2 capture. Blending hydrogen into fuels has attracted significant attention in the research of gas turbine and internal combustion engine power generation as it contributes to economy-wide decarbonization and bolsters the broader energy sources, especially green hydrogen. The present work carried out the thermodynamic analysis of a semi-closed sCO2 cycle to investigate how the hydrogen content in natural gas or syngas affects the operating parameters and performance. The results show that the energy efficiency decreases with increasing hydrogen content in natural gas whereas the maximum efficiency exists for the syngas with 60 % H2. The key factor is the increasing H2O content in the flue gas caused by adding hydrogen in fuels enhances both the heat-work conversion in the turbine and the heat transfer in the regenerator. The optimal turbine inlet temperature is around 1150 °C, which is the same as the basic cycle. The optimal turbine inlet pressure for natural gas and natural gas with 40 % H2 is both 28 MPa, while the optimal turbine inlet pressure decreases with hydrogen content in syngas. For all the fuels, the optimal turbine outlet pressure becomes lower for the higher hydrogen content. The maximum efficiencies obtained for natural gas, natural gas with 40 % H2, and syngas with 60 % H2 are 56.08 %, 55.52 % and 56.15 %. Finally, it is found that the recompression cycle and the multiple combustor arrangement (reheat cycle) cannot be the effective configuration for the semi-closed oxy-combustion sCO2 power cycle. The heat from the sCO2 recompression conflicts with the compression heat of the ASU, reducing the energy efficiency by 0.27 %, 0.34 %, and 1.23 % for the three fuels, respectively. The limitation of the regenerator allowable temperature requires the reheat cycle to either reduce the turbine inlet temperature or reduce the turbine outlet pressure, decreasing the energy efficiency for natural gas by 1.83 % and 6.38 % due to the reduced turbine output power or significantly increasing compression power.

Integrating machine learning and thermodynamic modeling for performance prediction and optimization of supercritical CO2 and gas turbine combined power systems

The supercritical carbon dioxide (SCO2) cycle has drawn attention to extracting energy and generating power from low-grade heat resources due to its higher efficiency, lower cost, and compactness. Combining the SCO2 cycle with a gas turbine (GT) is a promising field of research with applications in industries such as waste heat recovery (WHR) systems. In this research, three different configurations of power generation SCO2 cycles, including recuperation, precompression, and reheating, were thermodynamically designed and modeled. Extracting the main parameters of cycles, and the appropriate objective, which is cycle energy efficiency, up to 80,000 data constructed. Random forest (RF) and support vector regression (SVR), machine learning (ML) techniques, are used for the performance prediction of cycles. The results show the strength of the RF method to predict the cycle efficiency with up to 3% error and the SVR method with more than 90% accuracy. Sensitivity analysis and Particle Swarm Optimization (PSO) algorithm are employed for optimizing the recuperation cycle. The outcomes of the optimization model, based on the prediction models as proxies, have results in nearly close to those of traditional optimization, which is based on a thermodynamic model. In conclusion, ML models can be used in industry for prediction and maintenance since the methods are up to 5 times faster than thermodynamic models.

Genetic algorithm-based optimization of combined supercritical CO2 power and flash-tank enhanced transcritical CO2 refrigeration cycle for shipboard waste heat recuperation

The shipping industry significantly contributes to global trade and economy, but is also responsible for approximately ∼3 % of global greenhouse gas (GHG) emissions. Harnessing waste heat from marine vessels to perform useful work is a potential solution to reduce these emissions. Although the Organic Rankine Cycle (ORC) and CO2 cycles have been studied separately for waste heat recovery, a combined power and refrigeration systems, utilizing both cycles have not been reported. Herein, a combined system, “Marine Energy Recovery System (MERS)”, that integrates the supercritical CO2 Brayton power cycle with a flash-tank-enhanced transcritical CO2 refrigeration cycle, is proposed, aiming to generate power and provide cooling simultaneously. The power cycle incorporates an ORC, and a flash-tank is introduced within the refrigeration cycle to improve system performance. Both cycles share a low-temperature recuperator and a gas cooler to further utilize the heat between them. The MERS is evaluated from both a 1st and 2nd law perspective against various performance metrics under different operating conditions, such as: gas cooler pressure, evaporation temperature, and turbine inlet temperature and pressure. Results elucidated that the MERS achieved energy and exergy efficiencies of 54.62 % and 54.90 %, respectively, representing significant improvements over similar systems. The net work output improved by 717.55 kW and the net cooling capacity by 515.7 kW relative to the reference system. Furthermore, a COP of 2.99 outlines its potential as a cooling system. To further enhance MERS’s performance, a multi-objective optimization approach is employed, utilizing Artificial Neural Network (ANN) and Genetic Algorithm (GA). Optimal operational conditions yielded an energy efficiency of 74.95 % while maintaining a net work output of 6890.55 kW with gas cooler pressure, turbine inlet temperature, and gas cooler outlet temperature being 9.5 MPa, 461.76°C and 50°C respectively. These findings support the reliability and improved design of the MERS for future marine applications.