Supercritical CO2 Power Cycle Research Articles

Simulation and comprehensive study of a new trigeneration process combined with a gas turbine cycle, involving transcritical and supercritical CO2 power cycles and Goswami cycle

Simulation and comprehensive study of a new trigeneration process combined with a gas turbine cycle, involving transcritical and supercritical CO2 power cycles and Goswami cycle

Simulation of DME-O2 Combustion in a Hollow Cone Impinging Jet Combustor for Direct-Fired Supercritical CO2 Power Cycle

ABSTRACT Combustion is critical in the direct-fired supercritical CO2 power cycle. A hollow cone impinging jet combustor is designed. Instead of methane, dimethyl ether is used as the fuel for the direct-fired supercritical CO2 cycle, with a higher hydrocarbon ratio and oxygen. The dimethyl ether combustion process is simulated by Fluent, based on the k-ε turbulence model and Eddy-Dissipation Concept combustion model, combined with the dimethyl ether combustion mechanism. The effects of the CO2 recycling ratio, the excess oxygen coefficient, and in-combustor pressure are investigated to support improving combustion performance. The results indicate that the recycled CO2 intensifies the movement of the mixture in the combustor, reduces the peak temperature, and makes temperature distribution more uniform. As the excess oxygen coefficient increases, the peak temperature is enhanced, and the combustion is more sufficient. The effect of in-combustor pressure is complex. On the one hand, increasing in-combustor pressure reduces the jet penetration and inhibits the contact between dimethyl ether and O2, leading to a lower peak temperature. On the other hand, it prolongs the residence time of the high-temperature exhaust, making the reaction between dimethyl ether and O2 more sufficient. The optimal operating condition of the combustor is a CO2 recycling ratio of 0.95, an excess oxygen coefficient of 1.20, and an in-combustor pressure of 30 MPa. Moreover, the obtained combustion products parameters, such as temperature, component concentration, and mass flow rate, can guide the performance analysis for the direct-fired supercritical CO2 power cycle.

Performance and cost potential for direct-fired supercritical CO2 natural gas power plants

Direct-fired supercritical CO2 (sCO2) power cycles are being explored as an attractive alternative to natural gas combined cycle (NGCC) plants with carbon capture and storage (CCS). Therefore, understanding their performance and cost potential is important for the commercialization of the technology. This study presents detailed techno-economic optimization results of natural gas-fired, utility-scale power plants based on the direct sCO2 power cycle, which is lacking in public literature. The study considered multiple plant configurations with varying levels of thermal integration with the plant air separation unit (ASU) to shows the systematic impact of thermal integration on plant performance and economics. Several design variables for each power cycle configuration were identified and optimized to minimize the levelized cost of electricity (LCOE). The optimized direct sCO2 power plants achieved ∼48 % plant efficiency (HHV basis) which is similar or slightly higher plant efficiencies than state-of-the-art NGCC plants based on the F-class gas turbine with carbon capture and storage (CCS). The LCOE of the optimized direct sCO2 plants is 13–17 % higher than the reference NGCC plants with CCS due to high capital costs associated with the ASU and sCO2 power block, though there is significant room for improvement due to high uncertainty in component capital costs for these new plants. Based on the results, direct sCO2 power cycles have the potential to achieve >50 % efficiency (HHV basis) with >98 % CO2 capture rate which can lead to significant efficiency improvement and CO2 emissions reductions compared to NGCC plants with CCS.

Research on Off-Design Characteristics and Control of an Innovative S-CO2 Power Cycle Driven by the Flue Gas Waste Heat

Recently, supercritical CO2 (S-CO2) has been extensively applied for the recovery of waste heat from flue gas. Although various cycle configurations have been proposed, existing studies predominantly focus on the steady analysis and optimization of different S-CO2 structures under design conditions, and there is a noticeable deficiency in off-design research, especially for the innovative S-CO2 cycles. Thus, in this work aimed at the proposed novel S-CO2 power cycle, off-design characteristics and corresponding control strategies are investigated for the waste heat recovery. Based on the design parameters of the S-CO2 cycle, structural dimensions of printed circuit heat exchangers (PCHEs) and shell-and-tube heat exchangers are determined, and design values of turbines and compressors are specified. On this basis, off-design models for these key components are formulated. By manipulating variables such as cooling water inlet temperature, cooling water mass flow rate, flue gas inlet temperature and flue gas mass flow rate, cycle performances of the system are analyzed under off-design conditions. The simulation results show that when the inlet temperature and the mass flow rate of cooling water vary separately, the thermal efficiency both can reach the maximum value of 28.43% at the design point. For the changes in heat source parameters, the optimum point is slightly deviated from the design condition. Amidst the fluctuations in flue gas inlet temperature, the thermal efficiency optimizes to a peak of 28.56% at 530 °C. In the case of variation in the flue gas mass flow rate, the highest thermal efficiency 28.75% can be obtained. Furthermore, to maintain the efficient and stable operation of the S-CO2 power cycle, the corresponding control strategy of the cooling water mass flow rate is proposed for the cooling water inlet temperature variation. Generally, when the inlet temperature of cooling water increases from 23 °C to 27 °C, the cooling water mass flow should increase from 82.3% to 132.7% of the design value to keep the system running as much as possible at design conditions.

Thermodynamic Analysis of a Cogeneration System Combined with Heat, Cold, and Electricity Based on the Supercritical CO2 Power Cycle

The supercritical CO2 power cycle driven by solar as a new generation of solar thermal power generation technology has drawn significant attention worldwide. In this paper, a cogeneration system derived from a supercritical CO2 recompression Brayton cycle is proposed, by considering the recovery of waste heat from the turbine outlet. The absorption refrigeration cycle is powered by the medium-temperature waste heat from the turbine outlet, while the low-temperature waste heat is employed for heating, achieving the cascaded utilization of the heat from the turbine outlet. As for the proposed combined cooling, heating, and power (CCHP) system, a dynamic model was built and verified in MATLAB R2021b/Simulink. Under design conditions, values for the energy utilization factor (EUF) and exergy efficiency of the cogeneration system were obtained. Moreover, the thermodynamic performances of the system were investigated in variable cooling/heating load and irradiation conditions. Compared with the reference system, it is indicated that the energy utilization factor (EUF) and exergy efficiency are 84.7% and 64.8%, which are improved by 11.5% and 10.3%. The proposed supercritical CO2 CCHP system offers an effective solution for the efficient utilization of solar energy.

Effect of Impurities on the Compatibility of Steels in Supercritical CO2 at 450°–650°C

Abstract Direct-fired supercritical CO2 (sCO2) power cycles are a pathway to low-CO2 fossil energy but contain O2 and H2O in the sCO2 from combustion. The effect of impurities on structural steels was investigated at 450°–650 °C in 30 MPa sCO2. The test matrix included 9 and 12%Cr ferritic-martensitic (FM) steels and conventional and advanced austenitic steels exposed for 1000–2000 h with and without additions of 1%O2 and 0.1%H2O to simulate the cycle after water removal. For FM steels, the mass gains and scale thicknesses were similar with and without impurities with the formation of thick, duplex Fe-rich scales in all cases including the observation that Fe2O3 only formed with 1%O2. For the austenitic steels, higher mass gains were observed at all temperatures with increased formation of Fe-rich oxides when impurities were added. Carbon ingress was assessed by bulk combustion analysis, glow discharge optical emission spectroscopy (GDOES) and measuring postexposure room temperature tensile properties. Bulk C content was strongly increased at 650 °C but not at 450° or 550 °C.

Advanced exergy and advanced exergoeconomic analyses of the partial heating supercritical CO2 power cycle for waste heat recovery

Advanced exergy and advanced exergoeconomic analyses of the partial heating supercritical CO2 power cycle for waste heat recovery

Research on recompression supercritical CO2 power cycle system considering performance and stability of main compressor

The supercritical carbon dioxide (sCO2) power cycle has good prospects for use in many energy applications. Ensuring the stable operation of the power cycle is an important issue. The inlet condition of the main compressor in the sCO2 recompression cycle is close to the critical point of CO2 and the physical properties of CO2 change drastically near the critical point, so the study of inlet parameter change behavior of the main compressor is of great significance to the stable operation of the equipment and the system. This paper investigates the performance of an sCO2 recompression power cycle system under off-design conditions with different cooling and heating conditions. Unlike previous studies, this paper uses more accurate compressor and heat exchanger models to simulate the system for off-designed performance. A 1-D optimization prediction model of the compressor and a density-based segmented heat exchanger model are introduced to predict the performance changes of the system. The operating conditions, performance, and stability of the compressor under different cooling and heating conditions were compared. The results show that variations in different cooling and heating conditions change the inlet temperature of the compressor, causing the sCO2 compressor to deviate from optimal operation. As the inlet temperature increases, the power consumption of the compressor increases. At an inlet temperature of 305 K, the power is 1.93 MW (main compressor, MC) and 2.17 MW (recompressor, RC). When the inlet temperature increases to 310 K, the power increases by more than 10 %. The largest change in system efficiency is 3.76 % for a change in cooling conditions, and the largest change in compressor speed is 14.23 % (MC) and 7.79 % (RC) for a change in heating conditions, respectively. The operating condition of the main compressor moves far away from the surge line when its inlet temperature increases, which means the operation of the main compressor is more stable in this situation. The results of this paper contribute to the stable operation of the sCO2 recompression cycle.

Waste Heat Recuperation in Advanced Supercritical CO2 Power Cycles with Organic Rankine Cycle Integration & Optimization Using Machine Learning Methods

Supercritical CO2 (sCO2) stands out for concentrating solar power (CSP) due to its superior thermophysical and chemical properties, promising higher cycle efficiency compared to superheated or supercritical steam. Leveraging the waste heat from sCO2 cycles through the organic Rankine cycle (ORC) as a low-grade energy source enhances overall thermal efficiency. This research explores advanced sCO2 power cycles and introduces a novel approach by integrating machine learning and genetic algorithms for optimizing cycle performance. Utilizing a thermodynamic model-derived dataset, various machine learning algorithms, including Random Forest, XGBoost, and Artificial Neural Network are employed for prediction, evaluation and optimization. This innovative integration enables a comprehensive understanding of the complex dynamics of sCO2 power cycles. Subsequently, the study employs multi-objective optimization for the systematic evaluation and optimization of the combined power cycles, incorporating multiple bottoming cycles to maximize efficiency. The findings not only showcase the superiority of the unified sCO2ORC cycle but also emphasize the impact of integrating advanced computational methods in achieving optimal performance. The sCO2 cycle is explored in recompression, partial cooling, and main compression intercooling configurations. Recompression cycles utilize a single cooling system, while partial cooling and main compression intercooling layouts integrate a pair of ORCs at two precoolers. The ORC cycle enhances the recompression cycle through heat recuperation, extracting enhanced power originating from the bottom cycle. Critical parameters are taken into consideration to carry out optimization and performance evaluations. such as cycle temperatures, recuperator effectiveness, bottoming cycle pressure ratio, and condensation temperature. Results indicate that the combined partial cooling sCO2ORC cycle yields the optimal net output power of 7994.541 kW and thermal efficiency of 53.365 %. The findings highlight the capacity to propel and promote the utilization of waste heat recovery in energy technologies through enhanced and optimized power cycle designs, contributing to their advancement and widespread adoption.

Thermodynamic and exergoeconomic analysis of a dual expansion and triple recuperation supercritical CO2 power cycle driven by DME-oxygen combustor

A direct-fired supercritical CO2 power cycle with a novel layout and dimethyl ether (DME) as fuel is proposed, named the dual expansion and triple recuperation cycle (DETRC). To obtain accurate cycle simulation results, the combustion products’ state parameters and species concentrations are used as the inputs of cycle simulation, which are obtained from a three-dimensional combustion simulation. The performance of DETRC is compared with those of the direct-fired Allam cycle and other published direct-fired cycles. The effects of the CO2 recycling ratio, excess oxygen coefficient, in-combustor pressure, and turbine outlet pressure on the thermodynamic and exergoeconomic performance are investigated to obtain the optimal operating variables for DETRC.The results indicate that DETRC has excellent thermodynamic and exergoeconomic performance. Compared to the Allam cycle, the exergy losses of recuperators and coolers are reduced significantly, thermal efficiency is increased by 25.45 %, and the unit product cost is reduced by 18.31 % in the DETRC. Compared to the direct-fired cycles in the literature, the thermal and exergy efficiencies increase, and oxygen consumption reduces. The effect of the CO2 recycling ratio or excess oxygen coefficient on DETRC is non-monotonic. As the CO2 recycling ratio or excess oxygen coefficient increases, the thermal and exergy efficiencies increase and then decrease, and the unit product cost decreases and then increases. With in-combustor pressure increasing, the thermal and exergy efficiencies increase, unit product cost decreases, and the cycle performance is improved. As turbine outlet pressure increases, the thermal efficiency increases and then decreases, exergy efficiency increases, and unit product cost decreases and then increases. The optimal operating variables are that the CO2 recycling ratio is 0.95, the excess oxygen coefficient is 1.20, the in-combustor pressure is less than 30 MPa, and the turbine outlet pressure is 5.5 MPa.

Design Optimization of a Horizontal Particle Receiver for a Modular Beam Down Receiver CSP

CSP research is focused on increasing the economic competitiveness of this technology as compared to conventional and emerging energy generators. Higher temperature operation conditions represent a pathway toward cost reductions since they enable a relatively smaller solar field area (typically ~40-50% of the plant cost) for the same electrical output. For example, supercritical CO2 power cycles with solid particles as the HTF could enable >600°C operations and a ~50% power bloc cycle efficiency (considerably higher than steam cycles, <40%). Additionally, small modular systems could increase competitiveness through reduced financial risk, increased system flexibility, and the value of additional services that a modular CSP could offer to the electricity grid (frequency control, peaking supply, etc.). This study investigates the Beam Down Receiver (BDR) configuration as a design that could be well-suited to meet these goals while also overcoming some of issues with particle receivers, such as particle attrition, advective losses, and operation control. In particular, this work introduces a novel horizontal particle receiver (HPR) and analyzes the main design parameters, including tower height, BDR size, radiation flux on the receiver, and receiver nominal power. The analysis shows that tower heights between 35m to 60m are ideal for high temperature receiver capacities of 8-15 MWth, and that this configuration can achieve a minimized LCOH of ~24 USD/MWth. These results suggest that BDRs combined with particle mediums could represent a viable high temperature, high efficiency CSP alternative.

Performance evaluation of non-uniform twisted designs in precooler of supercritical CO2 power cycle

Twisted structures have been commonly used to improve heat transfer in tubular heat exchangers operating at regular pressures. However, their behavior under supercritical operating conditions remains unknown, and the thermal and hydraulic characteristics of a precooler equipped with twisted structures in a supercritical carbon dioxide (SCO2) cycle have not been studied before. For this reason, 3D simulations are conducted to explore the flow and heat transfer of SCO2 in a precooler featuring both twisted tubes and twisted tapes. Furthermore, four non-uniform configurations are designed for each twisted structure. The obtained results indicate that for SCO2 in a gas-like state, the use of twisted tubes is more suitable, whereas, for SCO2 in a liquid-like state, the use of twisted tapes is more appropriate. Twisted configurations exhibit a heat transfer coefficient ranging from 1.11 to 1.48 times higher than that of the straight mini-tube. Non-uniform structures can help control and tailor turbulence levels according to SCO2's thermophysical properties variations. The results reveal that shorter twist pitches at the beginning of the flow path in non-uniform twisted tubes and in the middle section for twisted tapes provide the best overall performance, with significant heat transfer enhancement and a relatively low pressure drop penalty.

Impact of Component Improvements Within a Next Generation sCO2 CSP Plant

Several component improvements within a next-generation CSP plant were investigated in the German-project, HelioGLOW, to determine their impact on the system performance. To accomplish this, multiple configurations of an upgraded CRS plant with four different components were parameterized and simulated using a transient simulation model. The four components introduced to the plant as upgrades are: a high temperature solid body receiver, an air curtain that reduces convection losses, a supercritical CO2 power cycle that can operate at a range of temperatures, and an advanced heliostat field. With the result of multiple annual simulations under various operating conditions, configuration optima, performance sensitivity and specific component improvements were identified.

Performance Analysis of High-Efficiency Supercritical CO2 Power Cycles Using Recompression

Abstract System simulation, parametric analysis, and exergy analysis were performed to identify the advantages and drawbacks of recompression in the direct-fired supercritical carbon dioxide (sCO2) power cycle. In a parametric investigation, the recompression ratio, turbine inlet temperature (TIT), and pressure ratio were changed, and the obtained values for the efficiency of the power cycle were compared. The TIT was varied between 600 °C and 1600 °C, revealing that recompression is highly effective for lower TIT values but is less effected at higher TIT values. For TITs above 1400 °C, the recompression cycle obtains almost no increase in efficiency. Different optimal recompression ratios were obtained for the different pressure ratios between the high- and low-pressure sides. Exergy analysis reveals that exergy destruction occurs primarily in the oxy-fuel combustor due to a chemical reaction and mixing of the high recirculation fluid. Higher TIT decreases the exergy destruction of the oxy-fuel combustor, but increases the exergy destruction in the lower temperature recuperator, and is not always favorable for obtaining efficiency improvements.

Optimization of a High Pressure Turbine Blade and Sector-Based Annular Rig Design for Supercritical CO2 Power Cycle Representative Testing

Abstract As part of the ongoing research into the design of hardware for zero emission cycles, a first-stage high-pressure turbine (HPT) blade is optimized for a 300 MWe supercritical CO2 (sCO2) power cycle using the surrogate-assisted genetic algorithm optimizer in Numeca FINE/Design three-dimensional with objectives of increasing efficiency and decreasing heat load to the blade. Supercritical CO2 property tables are constructed from NIST REFPROP data for the condensable gas simulation in FINE/Turbo. A detailed mesh sensitivity study is performed for a baseline design to identify the proper-grid refinement and efficiently allocate resources for the optimization. Seventy design variables are selected for the initial population generation. Self-organizing maps are then used to focus the design variables on the most important ones affecting the objective functions. The optimization results in approximately 3000 three-dimensional Reynolds Averaged Navier Stokes simulations of different blade shapes with increases in efficiency of up to 0.85% and decreases in heat load of 14%. Families of blade shapes are identified for experimental testing in an annular rig at the Purdue Experimental Turbine Aerothermal Laboratory. A design to adapt the annular cascade for testing optimized geometries is introduced, which features eccentric radius sectors allowing for scaled-up geometries of sCO2 optimized blade profiles to be tested at design cycle representative conditions at high Reynolds numbers in dry air. Analysis into the effects of Reynolds number, working fluid, and geometric relations are presented to prove the efficacy of the test method.

Demonstration of a small‐scale power generator using supercritical CO2

AbstractThe supercritical CO2 (sCO2) power cycle could improve efficiencies for a wide range of thermal power plants. The sCO2 turbine generator plays an important role in the sCO2 power cycle by directly converting thermal energy into mechanical work and electric power. The operation of the generator encounters challenges, including high temperature, high pressure, high rotational speed, and other engineering problems, such as leakage. Experimental studies of sCO2 turbines are insufficient because of the significant difficulties in turbine manufacturing and system construction. Unlike most experimental investigations that primarily focus on 100 kW‐ or MW‐scale power generation systems, we consider, for the first time, a small‐scale power generator using sCO2. A partial admission axial turbine was designed and manufactured with a rated rotational speed of 40,000 rpm, and a CO2 transcritical power cycle test loop was constructed to validate the performance of our manufactured generator. A resistant gas was proposed in the constructed turbine expander to solve the leakage issue. Both dynamic and steady performances were investigated. The results indicated that a peak electric power of 11.55 kW was achieved at 29,369 rpm. The maximum total efficiency of the turbo‐generator was 58.98%, which was affected by both the turbine rotational speed and pressure ratio, according to the proposed performance map.

Multi-objective performance optimization & thermodynamic analysis of solar powered supercritical CO2 power cycles using machine learning methods & genetic algorithm

The present study is focused on multi-objective performance optimization & thermodynamic analysis from the perspectives of energy and exergy for Recompression, Partial Cooling & Main Compression Intercooling supercritical CO2 (sCO2) Brayton cycles for concentrated solar power (CSP) applications using machine learning algorithms. The novelty of this work lies in the integration of artificial neural networks (ANN) and genetic algorithms (GA) for optimizing the performance of advanced sCO2 power cycles considering climatic variation, which has significant implications for both the scientific community and engineering applications in the renewable energy sector. The methodology employed includes thermodynamic analysis based on energy, exergy & environmental factors including system performance optimization. The system is modelled for net power production of 15 MW thermal output utilizing equations for the energy and exergy balance for each component. Subsequently, thermodynamic model extracted dataset used for prediction & evaluation of Random Forest, XGBoost, KNN, AdaBoost, ANN and LightGBM algorithm. Finally, considering climate conditions, multi-objective optimization is carried out for the CSP integrated sCO2 Power cycle for optimal power output, exergy destruction, thermal and exergetic efficiency. Genetic algorithm and TOPSIS (technique for order of preference by similarity to ideal solution), multi-objective decision-making tool, were used to determine the optimum operating conditions. The major findings of this work reveal significant improvements in the performance of the advanced sCO2 cycle by 1.68 % and 7.87 % compared to conventional recompression and partial cooling cycle, respectively. This research could advance renewable energy technologies, particularly concentrated solar power, by improving power cycle designs to increase system efficiency and economic feasibility. Optimized advanced supercritical CO2 power cycles in concentrated solar power plants might increase renewable energy use and energy generation infrastructure, potentially opening new research avenues.

Power Generation with Renewable Energy and Advanced Supercritical CO2 Thermodynamic Power Cycles: A Review

Supercritical CO2 (S-CO2) thermodynamic power cycles have been considerably investigated in the applications of fossil fuel and nuclear power generation systems, considering their superior characteristics such as compactness, sustainability, cost-effectiveness, environmentally friendly working fluid and high thermal efficiency. They can be potentially integrated and applied with various renewable energy systems for low-carbon power generation, so extensive studies in these areas have also been conducted substantially. However, there is a shortage of reviews that specifically concentrate on the integrations of S-CO2 with renewable energy, encompassing biomass, solar, geothermal and waste heat. It is thus necessary to provide an update and overview of the development of S-CO2 renewable energy systems and identify technology and integration opportunities for different types of renewable resources. Correspondingly, this paper not only summarizes the advantages of CO2 working fluid, design layouts of S-CO2 cycles and classifications of renewable energies to be integrated but also reviews the recent research activities and studies carried out worldwide on advanced S-CO2 power cycles with renewable energy. Moreover, the performance and development of various systems are well grouped and discussed.

Windage Loss Models for Enclosed Cylindrical Flows Under S-CO2 Condition

Abstract A supercritical CO2 (S-CO2) Brayton cycle is expected to have high compactness, simple configuration, and competitive efficiency. These advantages originated from CO2 nonideal gas properties near the critical point. However, the strong real gas effect makes the design challenging. Among components, turbomachinery is most affected by the real gas effects of S-CO2. In order to obtain accurate design of the turbomachinery, accurate loss models are needed. Windage loss is one of the external losses that determines the motor load and is responsible for heat generation due to friction. The overall turbomachinery efficiency is greatly affected by the windage loss especially in an S-CO2 power cycle due to high fluid density and high rotational speed. Therefore, an accurate windage loss model that can reflect the real gas effect of CO2 near the critical point is essential to obtain accurate design of the turbomachinery as well as the power cycle. In this paper, existing windage loss models are compared under S-CO2 conditions first, and the applicability of each model is evaluated. The comparison is to understand how much turbomachinery performance uncertainty can be expected due to the windage loss models and to suggest the way to improve the models.

Data-driven structural synthesis of supercritical CO2 power cycles

With new materials, objectives or constraints, it becomes increasingly difficult to develop optimal processes using conventional heuristics-based or superstructure-based methods. Hence, data-driven alternatives have emerged recently, to increase creativity and accelerate the development of innovative technologies without requiring extensive industrial feedback. However, beyond these proof-of-concepts and the promise of automation they hold, a deeper understanding of the behaviour and use of these advanced algorithms by the process engineer is still needed. In this paper, we provide the first data-driven solution for designing supercritical CO2 power cycle for waste heat recovery, a challenging industrial use case with lack of consensus on the optimal layout from the field literature. We then examine the issue of artificial intelligence acceptance by the process engineer, and formulate a set of basic requirements to foster user acceptance - robustness, control, understanding of the results, small time-to-solution. The numerical experiments confirm the robustness of the method, able to produce optimal designs performing as well as a set of selected expert layouts, yet only from the specification of the unit operations (turbomachinery and heat exchangers). We provide tools to exploit the vast amount of generated data, with pattern mining techniques to extract heuristic rules, thereby explaining the decision-making process. As a result, this paper shows how the process engineer can interact with the data-driven design approaches, by refocusing on the areas of domain expertise, namely, definition and analysis of the physical problem.