Due to the complexity of turbulent flow problems for film cooling, the traditional Reynolds average Navier-Stokes (RANS) method tends to underestimate the intensity of turbulent thermal diffusion, leading to inaccurate prediction of cooling effectiveness. A framework based on physics-informed neural network (PINN) was therefore proposed, and a data-driven neural network model of turbulent Prandtl number was built based on RANS flow data and large eddy simulation(LES) temperature data. After implementing this model into a RANS solver, the intensity of turbulent thermal diffusion could be adjusted dynamically and a temperature distribution highly consistent with LES results was obtained. Results show that PINN is an effective method to build a data-driven turbulence model and modeling of turbulent Prandtl number can effectively improve the accuracy of RANS temperature prediction.

The prospective demand for carbon reduction requires gas turbine combustion chambers to control NO_x emissions, improve power regulation range and fuel adaptability while outlet temperatures are continuously increasing. To address the above challenges, gas turbine manufacturers are developing axial staged combustion technology. This paper firstly introduced the principle of axial staged combustion and analyzed the effects of axial staged parameters, jet-in-crossflow flame morphology, nozzle geometry and fuel type on pollutant emissions and combustion instability. Existing studies show that reducing the equivalence ratio of the primary combustion chamber and enhancing the mixing uniformity of the secondary stage primary combustion chamber can reduce pollutant emissions. The thermoacoustic oscillation of axial staged combustion chambers is complex, and could be inhibited by a reasonable selection of stage parameters. The emission reduction benefits and part-load flexibility of axial staged combustion chambers have been verified in commercial operation. Based on the current research status, key issues and future research directions of axial staged combustion technology are proposed.

Heavy-duty gas turbine is a kind of efficient thermo-mechanical conversion equipment so far, with the combined cycle efficiency higher than 60%. As gas turbines have excellent peak shaving capability, they will play an increasingly important role in the new power network based on new energy. An overview of the working characteristics, the structural features and main technical parameters of heavy-duty gas turbine compressors were introduced. The development and technical progress of typical gas turbine compressors from major international original equipment manufacturers were reviewed. The research progress of compressor design system was summarized. Considering the development of advanced heavy-duty gas turbine technology, key technology development directions were proposed, including aerodynamic layout optimization, high performance airfoil, full 3D design of transonic stages and highly integrated design system, based on the development status of heavy-duty gas turbines in China.

Due to the uneven distribution of combustion temperature field in the operation processes of thermal power plants, issues such as over-temperature, tube explosion and flue gas corridor of the furnace heating surfaces may occur. By evaluating the temperature field distribution of the boiler during operation processes, the combustion adjustment can be made to improve the safety, stability and economy of the boiler operation when the operation status can be examined timely. With the boiler of a 660 MW ultra-supercritical power plant as an example, the combustion optimization adjustment test and simulation were carried out. Temperature of heating surfaces and the wall temperature change at the burner were analyzed, and the wind speed and pulverized coal concentration deviations of powder pipes in the pulverizing system, internal and external secondary air volume and intensity of the burner, the adjustment of the direct current air volume, and the wall air in the furnace were measured. Results show that the factors, such as the combination operation modes of different coal mills and the modes of secondary air distribution have a great impact on the boiler operation. In particular, the wall over-temperature, the burner temperature and reducing atmosphere on the heating surface are influenced, which will affect the boiler economic operation. After adjustment, the wall over-temperature phenomenon of the screen superheater, high temperature superheater and high temperature reheater disappears, there is no burnout of burners, and the amount of NO_x generation is also within a reasonable range.

An integrated energy system using solid oxide fuel cell (SOFC)/gas turbine (GT) as power generation device and hydrogen-doped natural gas as the fuel was proposed. The mathematical models of various types of energy utilization equipment, such as wind power generation, solar power generation, hydrogen production equipment, SOFC/GT system, energy conversion and storage equipment for electricity, heat, and cooling, carbon capture equipment, etc, were established. The performance and economy of the integrated energy system were studied considering various load balance constraints, equipment operation constraints and aiding in achieving the "dual carbon" targets. Results show that the power generation efficiency of SOFC/GT system increases from 60.36% to 64.79%, and the comprehensive energy utilization rate increases from 87.80% to 90.80% with the increase of fuel hydrogen blending ratio. When the system used renewable energy sources to produce hydrogen, the carbon emissions are the lowest, although carbon trading gains are considered, the high cost of hydrogen production leads to the highest operating costs.

To explore the deep peak shaving capacity of coal-fired boilers, the hydrodynamic force and wall temperature characteristics of the water-cooled wall of a supercritical 630 MW boiler were studied. Mathematical models of the hydrodynamic force and wall temperature characteristics were established, and water-cooled wall pressure drop, flow distribution, outlet working substance temperature and wall temperature distribution along the furnace height between 20% and 30% boiler maximum continuous rating (BMCR) loads were analyzed. Results show that, the helical tube sections of the water-cooled wall exhibit small thermal deviation and uniform heat load distribution under 20% and 30% BMCR loads. The outlet steam temperature deviation of the vertical tube sections of the water-cooled wall is large, and the over-temperature is more likely to occur in this area. Under 30% BMCR load, the boiler could operate safely in dry state condition. Under 28.8% BMCR load, the inlet water temperature of the water-cooled wall is 280.0 ℃, and the maximum wall temperature of the water-cooled wall in dry state condition exceeds 450.0 ℃. Under 27.3% BMCR load, the maximum wall temperature of the water-cooled wall in dry state condition exceeds 500.0 ℃, and the boiler should operate in wet state condition or the wall temperature should be reduced by adjusting the inlet water temperature.

As the heart of the gas turbine, the central rod-fastened rotor operates under harsh conditions with frequent incidents, necessitating a rigorous exploration of its strength under complex contact states across multiple scales and loads to ensure the safe functioning of the disc structure. Employing a rough surface contact model and three-dimensional finite element methods, a thermo-mechanical coupling analysis model for the gas turbine disc's Hirth tooth contact interface was developed, incorporating microscale interface dimensions and surface roughness. Results show that the maximum equivalent stress of the end face teeth decreases with the increase of the root fillet radius and the decrease of the pressure angle; the maximum equivalent stress and average contact pressure of the end face teeth decrease with the increase of surface roughness.

In order to analyze the influence of inflow distortion on flutter characteristics of gas turbine compressors, an inlet total pressure model with radial distortion was established. Based on the influence coefficient method, the effects of radial inflow total pressure distortion with different phases and distortion intensities on the flow field characteristics and aeroelastic stability of compressors were studied. Results show that the radial inflow total pressure distortion with phase angles of 90° and 180° will increase the minimum value of aerodynamic damping under dangerous conditions, and the aeroelastic stability is improved. The radial inflow total pressure distortion with phase angle of 180° can improve the aeroelastic stability of the compressor at all inter blade phase angles. However, the radial inflow total pressure distortion with phase angles of 0° and 270° will increase the risk of compressor flutter,which should be avoided.

Aiming to reduce carbon emissions for environmental sustainability, hydrogen-blended combustion has emerged as a pivotal advancement in gas turbine technology. Focusing on the hydrogen-blended natural gas combustion characteristics, comprehensive full-temperature, full-pressure, and full-scale combustion tests with a hydrogen-enriched ratio were conducted on an independently developed DeNO_x burner of F-class heavy-duty gas turbine. The burner's adaptability to hydrogen-blended combustion was analyzed based on performance parameters such as temperature, emissions, humming, and acceleration. Results show that within a hydrogen blending range of 30% to 40%, the NO_x emissions from this burner can be controlled below 30 mg/m³ across the base load range of 55% to 100%. As the hydrogen blending ratio increases, flame transition occurs at a lower load, which is conducive to stable load increases. Furthermore, the outlet temperature of the burner rises, but no flashback occurs.

To improve the thermodynamic performance of the heavy duty gas turbine with bleed air, a novel gas turbine system with high effective utilization of bleed air energy was proposed, and the change of thermodynamic performance was researched. Taking the performance data of a traditional typical F-class gas turbine under different ambient temperature conditions as the comparison reference, for the novel gas turbine with high effective bleed air cooling, the changes of performance indicators of the total system were analyzed with different design parameters of cooling system by numerical simulation, while the thermodynamic performances under three operation modes were calculated and compared. Results show that the temperature of bleed air from compressor can be effectively decreased by adopting the novel gas turbine system with high effective utilization of bleed air cooling, and the thermodynamic performance of gas turbine is further improved. Under summer condition, when the inlet air temperature is cooled to 30, 20, and 15 ℃, respectively, the output power is increased by 25.92, 40.49, and 48.22 MW, and the efficiency of gas turbine is improved by 0.78, 1.19, and 1.40 percentage points.

Influence of hole configuration including cylindrical, fan-shaped and laidback fan-shaped holes on effusion cooling performance under different pressure drops of cooling air was examined using infrared thermal imaging technology. Results show that due to the vortex impact effect, low local cooling efficiency areas appear on the wall surface, which are independent of the hole type. The change in hole type only affects the cooling effect of the wall surface. Increasing the pressure drop of the cooling air can improve the cooling effect, and the area of the low cooling effect zone also decreases accordingly. The difference between the cooling hole shape and the pressure drop of the cooling air causes the movement of the lowest cooling effectiveness position on the wall. As the velocity of cooling air increases, this point moves upstream. In terms of the uniformity, the minimum effectiveness of cylindrical holes is lower by 14.3% to 27.5% than the area-averaged one. The difference between the minimum cooling efficiency of the fan-shaped hole, the expansion hole and the average level is greater, and the uniformity of the cooling effect is worse. The comprehensive cooling efficiency of the expansion hole is the highest, but the uniformity is the worst.

For the supercritical carbon dioxide (S-CO₂) with heated flow in a horizontal tube, to research the influence of the buoyancy effect on flow and heat transfer characteristics, experiments were conducted on flowing and heating in optical and inner coiled wire tubes under the same condition. Investigations were carried out for the influence of the wall heat flux density and mass velocity on the buoyancy effect, while discussions were given for the influence of the inserted coiled wires on the wall temperature distribution, heat transfer mode, etc. Results show that the temperature stratification caused by the buoyancy effect occurs along the gravity direction during SO₂ horizontal flowing with heating, which leads to the severe wall temperature divergence at the top and bottom, with a maximum wall temperature difference of up to 48 K. The inserted coiled wires in tube can effectively inhibit the temperature stratification caused by the buoyancy effect, while the heat transfer coefficients at the bottom and top are increased by more than 60% and more than 140%, respectively. Based on the validation of experimental results with four heat transfer correlations, it is found that Bishop correlation has the best comprehensive performance.

Taking the F-class gas turbine compressor as the research object, the performance degradation mechanism of multi-stage axial compressor at different states of corrosion/ware was studied by three-dimensional numerical simulation, considering the changes in blade tip clearance caused by corrosion and wear during actual operation of gas turbine. The influence of tip clearance on the performance of multi-stage axial compressor was analyzed. Results show that the increase of tip clearance causes the characteristic curves of the compressor to move towards the direction of mass flow reduction as a whole, resulting in certain degree of decline of mass flow, efficiency and pressure ratio. With the increase of tip clearance, the compressor maximum efficiency decreases gradually, and the surge margin decreases obviously. The increase of tip clearance also results in intensified flow separation inside the compressor, and the change of tip clearance of rotors has more serious impact on flow separation inside the compressor. The flow separation near the trailing edge of the suction surface of stators leads to the formation of a low Mach number region, and the loss near the stator root increases obviously due to the countercurrent low-speed vortices, resulting in the decline of compressor performance.

Taking IEA 15 MW floating offshore wind turbine and UMaine VolturnUS-S semi-submersible platform as research subjects, a structure design process of wind turbine floating platform was proposed in this study. The stability analyses on the dimensional parameters of each component in the floating platform were conducted using Ansys Aqwa hydrodynamic analysis software and OpenFAST simulation analysis software. The impact of column spacing, side column height, side column diameter, pontoon height, pontoon width, and heave plate diameter on the overall dynamic response of wind turbine system and mooring cable tension was investigated. The effect of dimensional changes on the stability of wind turbine system was explored. Results show that increasing the column spacing and side column diameter can significantly enhance the overall stability of floating wind turbine system during the operation. The changes of side column height above the waterline have almost no impact on the stability of wind turbine system. Pontoon width and pontoon height primarily affect the motion response in the heave direction, while increasing the heave plate diameter significantly improves the longitudinal and heave direction stability of floating platform.

A turbine with high cycle fatigue failure was used as the simulation model, the coupling method of three-dimensional unsteady flow field and solid vibration response analysis was adopted, the simulation of fault point was carried out. According to the different conditions of turbine expansion ratio and turbine reaction force, the law of aerodynamic load distribution and aerodynamic exciting force caused by aerodynamic state change was compared, at the same time, the relative variation trend of blade vibration stress was obtained. Results show that under unchanged intake conditions, the average exciting force, the amplitude of exciting force and the vibration stress of the blade increase obviously with the increase of the expansion ratio of the turbine. While the turbine reaction force increases, the average aerodynamic exciting force of the blade increases obviously, but the amplitude of the exciting force and the vibration stress have a downward trend.

To solve the problem of ANSYS-Fluent software being unable to provide both high-precision and high-efficiency radiation spectrum models, secondary development was carried out for the full-spectrum correlated-k distribution (FSCK) model based on look-up table method and machine learning method, and the model was embeded into Fluent and coupled with built-in radiative transfer equation (RTE) solvers for radiation heat transfer calculation for mintures of common combustion gases and soots. Radiation heat transfer results of one-dimensional slabs and two group of flames were calculated by the model, and using the line by line (LBL) model as a benchmark, which were compared with the results calculated by gray gas weighted sum (WSGG) model in Fluent. Results show that the FSCK model yields more accurate solutions than the built-in WSGG model in Fluent, regardless of the presence of soot.

In order to investigate the impact of key parameters on the thermodynamic performance of both the overall and critical components of a hydrogen-blended heavy-duty gas turbine, a thermodynamic performance calculation model was established,and the definitions and settings of the key parameters in the moldel were explained. By examining different hydrogen blending ratios, turbine inlet temperatures, compressor pressure ratios, and cooling air volumes, the study assessed their influences on the power output and thermal efficiency of gas turbine. Additionally, changes in turbine aerodynamic parameters under different hydrogen blending ratios were analyzed, and the mechanisms behind the impact of hydrogen blending on gas turbine performance were further revealed. The results show that the mixing ratio of hydrogen, turbine inlet temperature, pressure ratio and cooling air quantity are the key parameters that affect the performance of heavy duty hydrogen blended gas turbine; and the changes in aerodynamic parameters of the turbine such as turbine flow angle and outlet Mach number caused by the hydrogen blending ratio changing will affect the aerodynamic performance of the turbine and the thermodynamic performance of the gas turbine.

This study focuses on the squealer tip film cooling design of turbine blades, presenting three layouts: two with full ribs, one with a full rib and a half-rib on the pressure side, and one with a half-rib on the suction side. Using numerical simulations through three-dimensional Reynolds-Averaged Navier-Stokes (RANS) equations and a standard k-ω turbulence model,the heat transfer and cooling performance of grooved blade tips with two full rib layouts were studied under four different blowing ratios.The aerodynamic and heat transfer performance, as well as film cooling effectiveness of blade squealer tip with different rib layouts and typical squealer tip without rib layout were compared and analyzed at blow ratio 1.0 condition. Results show that the distribution of heat transfer coefficient at the blade tip predicted by numerical methods is in good agreement with the experimental measurement results, which verifies the reliability of the numerical method; at a blowing ratio of 1.0, the squealer tip with full ribs exhibits the highest average film cooling effectiveness, surpassing the typical groove design by 2.2% in effectiveness. The layout with half ribs on the pressure side shows the lowest average heat transfer coefficient and total pressure loss. Rib configurations markedly alters the flow structure over the leaf top, thereby affecting its aerothermal performance and film cooling effectiveness, with the full rib layout displaying optimal overall aerothermal performance and cooling effectiveness.

Axial fuel staging (AFS) combustion technology is an advanced low pollution combustion technology for heavy gas engines at present. In order to reveal the effects of H₂/CH₄ fuel species and jet angle on the re-combustion zone flow field and flame structure of axial staged combustion, high-frequency particle image velocimetry (PIV) and OH^*-based self luminescence techniques were used. The effects of 90° and 45° jet angles on the axial staged flow field and the flame structure of different fuels were investigated when the jet equivalence ratio was 0.6 and the momentum flux ratio was 6. Results show that when the jet angle is 90°, there will be an obvious recirculating zone at the root of the jet, and the jet flames have periodic pulsations. When the jet angle is 45°, the shear layer will not produce a significant recirculating zone at the root of the jet, the jet flame burn is more stable, and the chemical residence time of the fuel in the low-speed zone is shorter, which has better adaptability for hydrogen fuel with fast flame propagation speed and easy tempering. The doping of methane fuel with hydrogen increases the propagation speed of the jet flame. With the increase of hydrogen doping ratio, the jet flame gradually changes from a detached flame to a continuous flame, the jet flame branch appears on the windward side, the length of the reaction zone is shortened and smaller, the flame intensity is enhanced, and the flame root moves to the nozzle outlet and finally attaches to the jet nozzle outlet.

The flow heat transfer and cooling characteristics of hydrogen-fired gas turbine were analyzed under coupled action of heat conduction/convection/radiation. A weighted sum of gray gases (WSGG) model was developed to calculate the high ratio of water vapor and carbon dioxide partial pressure. Results show that the increase of water vapor content in the working fluid of hydrogen-fired gas turbine leads to the increase of metal wall temperature. After adding the influence of radiation, the effect of water vapor and carbon dioxide contents on heat transfer is opposite, which is mainly due to the fact that carbon dioxide has a stronger convective heat transfer capacity than water vapor, while water vapor has a stronger radiative capacity than carbon dioxide. Meanwhile, in the hydrogen-fired turbine cooling coupled system with three heat transfer modes of convection-conduction-radiation, the film cooling velocity field is almost unaffected, while the temperature field is deeply affected by coupling effect and radiation. The gas film cooling efficiency under coupled condition defined in this paper can characterize the gas film cooling performance under the condition of hydrogen combustion. Therefore, in the design of hydrogen combustion turbine cooling, the thermal load deterioration caused by hydrogen combustion should be included in the design variables.

To address the response issues caused by time lag and load fluctuations in NO_<i>x emission control of SCR denitrification system, reinforcement learning was employed to adjust the proportional-integral-derivative (PID) parameters. The loss function of Critic network was redesigned according to the deep deterministic policy gradient (DDPG) algorithm, and a delay queue was introduced to simulate system latency. The proposed control strategy has been applied to a 660 MW ultra-supercritical coal-fired power unit in China. Results show that the reinforcement learning control method is superior to traditional PID control in terms of adjustment time, overshoot, and stability. The proposed strategy overcomes the time lag and load fluctuations that traditional PID control cannot resolve, demonstrating the significant theoretical and practical values.

From the perspective of gas turbine blade cooling design, the study and application progresses of data-driven methods of domestic and foreign researchers in recent years was summarized. Three types of data-driven methods including mathematical statistics, machine learing and deep learning were introduced. The advantages of data-driven methods over experimental and numerical simulations were expounded. And the application of data-driven methods was emphatically summarized, mainly including predicition and uncertainty quantification of turbine blade cooling characteristics, improvement of turbulence models in numerical simulation, and data fusion of existing data and knowledge. Based on the current research hotspots and development tendency, further studies focus on data-driven methods in gas turbine blade cooling design were proposed, including exploring the potential of data fusion approches, improving generalization ability, reducing data cost, studying data processing methods, comparing the advantages and disadvantages of different data-driven methods, and developing data-driven approaches for complex cooling designs.

Experimental studies were conducted on two types of micro-mixing diffusion combustors, one with a swirl number of 0.62 and another one without swirl, under the equivalence ratio from 0.3 to 0.5. The influences of swirl on the flow field distribution, flame structure, NO_x concentration, and combustion instability of micro-mixing diffusion combustion were investigated experimentally. The methods of OH^* chemiluminescence and particle image velocimetry (PIV) were used to capture flames and flow structures. Results show that adding swirl can reduce the flame height by 44% and shorten the residence time by changing the flow field structure, ultimately achieving a 63.4% reduction in NO_x emissions. Without swirl, the main driving factor of micro-mixed diffusion flame pulsation is the formation of radial expansion zone under high equivalent ratios, while swirling flow can inhibit the formation of radial expansion zone, so as to achieve the effect of suppressing combustion oscillation in a wide load range.

The axial staged combustion chamber of the self-developed F-class gas turbine was studied under full temperature and full pressure condition. In order to explore the combustion performance of the combustion chamber under the working conditions of the design point, such as pressure loss, outlet temperature distribution, wall temperature, pollutant discharge, combustion efficiency and thermoacoustic stability,etc. Results show that, the total pressure loss coefficient of the combustion chamber is 5.4% at the design point. The outlet temperature distribution factor and radial temperature distribution factor are 0.06 and 0.03, respectively. And the wall temperature of the flame barrel in the combustion chamber is below 850 ℃. The mole fraction of NO_x is maintained 1.9×10^-5, while the emissions of CO and unburned hydrocarbon(UHC) are basically zero. The combustion efficiency is maintained above 99.99%. The amplitude of dynamic pressure spectrum is below 3 kPa, which indicates the thermoacoustic state of the combustor is stable.

The flow field near the endwall of gas turbine cascade presents extremely complicated three-dimensional characteristics, and the endwall cooling design needs to consider not only the effects of the strong secondary flow of the endwall on the cooling performance, but also the effects of the cooling layout on the flow and heat transfer characteristics of the proximal endwall. In view of the cooling demand for the gas turbine cascade endwall, a combination of numerical simulation and experimental test were used to systematically investigate the effects of discrete air film holes, leakage flow and endwall modification on the endwall surface film cooling, heat transfer, flow and cascade aerodynamic characteristics under different mass flow ratios. The results show that, the film cooling effectiveness of the endwall can be effectively improved by the appropriate injection angle and layout of the film holes, the geometric structure of the leakage flow cooling unit and the addition of micro-scaled ribs on the endwall surface. The leakage flow from upstream slot and rim seal can provide cooling protection for the upstream and the area near the suction surface of the upper half of the endwall, while the leakage flow from mid-passage gap will protect the rear half endwall near suction side well. The arrangement of fan-shaped air film holes and the curved assembly gap can not only improve the effectiveness of film cooling, but also effectively control the aerodynamic losses.

Taking the combustor liner of F-class gas turbine as the research object, analysis was carried out on the internal flow field, temperature field and stress field of the combustor liner under rating operation conditions based on fluid-thermal-solid coupling method, considering the effect of thermal barrier coatings and cooling structures on the aerodynamic heat transfer of the combustor liner. The results of numerical analysis were compared with the actual damage situation of the combustor liner. Results show that the high stress areas are basically consistent with the actual damaged regions of the combustor liner, thus the fluid-thermal-solid coupling method can be used to predict the damage situation of the combustor liner. The ceramic layers of the thermal barrier coatings at different locations have similar insulation effect. Both the substrate and the ceramic layers of the thermal barrier coatings in the vicinity of the cooling structures are areas of high stress.

Considering the impact of multi-factor coupling in the power market on power price forecasting, a power market price forecasting model based on long-short term memory (LSTM) neural network was established. The historical new energy output, power transmission, power load and other factors affecting the power supply and demand relationship were set as the boundary factors of LSTM learning parameters, and data preprocessing was carried out. The model parameters of LSTM neural network, including the number of layers, iteration times and learning rate, were optimized to generate a training model for electricity price forecasting, which was then used to forecast the electricity price curves for trading days. The correctness of the proposed method was verified through example simulation, a prediction scenario for electricity trading in a spot market province was constructed, and the evaluation indicators of power price forecasting accuracy were introduced. The results indicate that this method provides a reference for research on day-ahead clearing price prediction and offers market participants in the electricity market effective bidding strategies to achieve substantial marketing revenue.

To enhance the energy efficiency of the thermal energy storage system using superheated steam to heat molten salt, a coal-fired unit system configuration integrating the three-tank molten salt thermal energy storage system was proposed. The flexibility improvement potential of coal-fired power plant and the thermodynamic performance of the integrated system were analyzed under typical charging and discharging conditions. Results show that under the condition of 30% THA for the charging process, the maximum output power of coal-fired power plant can be reduced by 81.60 MW, accounting for 12.36% of the rated load, due to the limitation of the minimum steam flow rate through the low-pressure turbine. Under the condition of 50% THA for the discharging process, the maximum output power of coal-fired power plant can be increased to 52.45 MW, accounting for 7.95% of the rated load. The equivalent round-trip efficiency of the integrated system is influenced by the discharging condition. The maximum equivalent round-trip efficiency is 75.35% at the discharging condition of 50% THA, while the minimum equivalent round-trip efficiency is achieved at 59.43% at the discharging condition of 100% THA.

In order to solve the problems of low speed and low accuracy of rolling bearing fault diagnosis caused by the inconsistent sampling frequency of the accelerometer of mechanical vibration monitoring system, a rolling bearing fault diagnosis method based on variational mode decomposition-multi-strategy tuna swarm optimization-extreme gradient boosting (VMD-MTSO-XGBoost) at wide sampling frequency was proposed. Firstly, the vibration signal was de-noised by wavelet and de-sampled to get the de-noised signal at wide sampling frequency. The de-noised signal at wide sampling frequency was processed by variational mode decomposition (VMD), and the intrinsic mode function (IMF) component index was extracted to form the fault feature vector. Secondly, the Circle chaotic map was used to initialize the tuna swarm optimization (TSO) population to increase the richness and diversity of the initial population. In order to improve the ability of the algorithm to jump out of the local optimum and enhance the ability of the algorithm to explore the whole world, the dimension-by-dimension mutation method was used to disturb the optimal individual position. Finally, the modified tuna swarm optimization (MTSO) algorithm was used to optimize the parameters of extreme gradient boosting (XGBoost), and the rolling bearing fault diagnosis model was established. The proposed fault diagnosis method was validated by the Case Western Reserve University dataset, the German University of Paderborn dataset and the measured dataset. Results show that at wide sampling frequency, the fault diagnosis method presented in this paper can identify rolling bearing faults more efficiently and accurately compared with the other three models.

To address the difficulty of fault diagnosis in thermal power equipment with multi-parameter coupling and gradual changes, a fault early warning method based on least absolute shrinkage and selection operator (LASSO) regression feature selection and bidirectional long-short term memory (BiLSTM) multivariate regression prediction was proposed. Taking a coal mill in a 1 000 MW power unit as the research subject, feature parameters such as mill current, outlet pressure, and inlet-outlet differential pressure were selected to represent blockage faults. LASSO regression was employed to select the feature variables, and a multivariate regression prediction model was established based on the BiLSTM algorithm. According to the variation mechanism of the feature parameters during mill blockage and the predicted values of the model, a mill blockage fault index was constructed. Finally, the warning threshold was determined using the kernel density estimation method, enabling mill blockage fault warnings. Actual data analysis shows that when the coal mill is operating normally, the average relative error of the BiLSTM multivariate regression prediction model is 1.13%. Compared with the traditional error back-propagation (BP) neural network and support vector regression (SVR) model, it has higher accuracy and the ability to predict the trend of parameter change. When the coal mill is operating abnormally, this method can detect operational abnormalities earlier than the multivariate state estimation technique (MSET) algorithm model, enabling early fault warning under variable operating conditions of the coal mill.

In order to verify the feasibility of blending a large proportion of ammonia in a coal-fired unit, a numerical simulation model was established using a 660 MW wall type tangentially-fired boiler as an example. The impact of ammonia blending ratio, ammonia injection location, and primary and secondary air distribution methods on combustion in the furnace was analyzed. Results show that blending ammonia in coal-fired boiler leads to a decrease in flue gas temperature and an increase in NO_x mass concentration in the furnace. The greater the ammonia blending ratio, the more significant the decrease in flue gas temperature and the increase in NO_x mass concentration. When the ammonia blending ratio increases to 40%, the average flue gas temperature in the furnace drops by approximately 50 K, and the outlet NO_x mass concentration increases by 29.4%. Measures such as blending ammonia in higher-level burners and increasing the primary air ratio can reduce the NO_x mass concentration at the furnace outlet while ensuring complete combustion of ammonia and coal.

Phase change materials (PCM) are effective materials for thermal energy storage with a wide range of application prospects. However, their inherent low thermal and electrical conductivity greatly hinder their practical application in the field of thermal energy storage. By compositing PCM with different energy conversion materials, efficient mutual conversion among various forms of energy and thermal energy has been achieved. The composite PCM plays a key role in solar photothermal/electrothermal conversion and storage. In the field of photothermal conversion, the compositing of high thermal conductivity photothermal conversion materials with PCM has optimized the thermal conductivity and effectively enhanced the heat storage capacity, photothermal conversion efficiency, and solar energy utilization efficiency. In the field of electrothermal conversion, the preparation of electrothermal composite phase change materials by introducing high electrical conductivity supporting materials has not only improved the electrothermal conversion efficiency but also enriched the utilization methods of electrical energy. A detailed review of the latest research progress on photothermal and electrothermal conversion materials was provided, and the materials were classified. Aiming to offer new insights for the advancement of energy storage technology, the advantages and disadvantages of various types of materials were analyzed, the mechanisms for improving thermal energy conversion efficiency were revealed, and future development directions and challenges were prospected.

To meet the demand for flexible regulation performance of traditional thermal power units, a data-driven nonlinear environmental modeling method for supercritical combined heat and power (S-CHP) and a reinforcement learning control method based on double-delay deep deterministic strategy gradient (TD3) were proposed. Firstly, a data-driven nonlinear model environment was established based on the deep learning algorithm of multi-layer perceptron (MLP) and the dynamic characteristics of the S-CHP unit. Furthermore, based on deep reinforcement learning algorithms, an actor critic strategy value network and S-CHP specific state values and reward functions were designed to conform the dynamic characteristics of the S-CHP unit. A flexible control strategy of TD3 was proposed to achieve the control objectives of rapid response, ensuring heating supply and stable operation. Results show that compared with single-layer networks, the MLP model reduces the root mean square error by 51.7% at the rated power of 52%-93%. Compared with the traditional coordinated control method, the TD3 control strategy has better tracking effect and higher response rate.

Taking a certain gas-fired heater as the research object, synergistic rules of NO_x and CO₂ production under different proportions of biomass gas co-firing were studied. Results show that compared with pure gas combustion, co-firing biomass gas can reduce furnace flame center, peak temperature of furnace flue gas and outlet flue gas temperature of the convection chamber. When the co-firing ratio is 10%, the volume fraction of carbon decreases by 25.3%, and the volume fraction of NO_x at the outlet is reduced by 67.1%. When the co-firing ratio exceeds 10%, the outlet NO_x production decreases slowly. When the co-firing ratio is 5%-10%, the CO₂ and NO_x production shows a positive synergistic trend, while when the co-firing ratio is within the range of 15% to 30%, the generation amounts of CO₂ and NO_x show a negative synergistic trend. Therefore, to synergistically reduce the generation amounts of CO₂ and NO_x, the optimal co-firing ratio is 10%. At this ratio, the furnace outlet volume fraction of CO₂ is the lowest(2.30%), and the volume fraction of NO_x emissions is 49.8×10^-6.

Wave is a main contributor to the power fluctuations in floating offshore wind turbines (FOWTs), and therefore challenges the large-scale grid integration of FOWTs. To reduce the impact of waves on wind turbine power, a power control method for floating turbines based on wave interval estimation and prediction was proposed. Focusing on the rated power tracking control of the FOWT above the rated wind speed, a FOWT model with input time delay under large inertia and a wave disturbance model were established, a wave predictor based on wave interval estimation was designed, and then a composite time-delay control strategy was developed combining wave compensation and integral sliding mode control. The operation of a semi-submersible FOWT under the present control strategy was simulated using a FAST-Matlab/Simulink co-simulation environment and compared to the system response under traditional PI control. Results show that the proposed power control strategy can effectively compensate for the impact of wave disturbances on FOWTs, significantly reduce power output fluctuations, and provide a reference for the design of control systems for floating wind turbines.

To address the problems of insufficient accuracy and stability of the existing photovoltaic (PV) power prediction models, a PV power prediction model was proposed. This model was based on sky image data, the simple model of the atmospheric radiative transfer of sunshine (SMARTS), and the LK optical flow method. The SMARTS was used to calculate the clear sky irradiance and solar position information at a specified time, and the cloud motion vectors were obtained through the LK optical flow method. The cloud motion vectors were used to infer the shading situation of the cloud to the direct sunlight at future times. Then, the clear sky irradiance and the predicted solar shading situation were used to calculate the final power prediction result. The model was validated using the sky image dataset SKIPP'D. In a sunny environment, the proposed method was compared with the Bird model and the Ineichen model. In a cloudy environment, the proposed method was compared with the long short-term memory (LSTM) neural network model and the convolutional neural network (CNN) model. The effectiveness of this method in short-term PV power prediction has been verified. Results show that, the proposed method can accurately capture the effect of cloud changes on the PV power generation in a cloudy environment, the determination coefficient R² of the model is greater than 90%, and both the prediction accuracy and stability are significantly better than those of the control models.

Aiming at the problem of early fault diagnosis of rolling bearings, a fault diagnosis method of red-tailed hawk (RTH) algorithm optimization with feature mode decomposition (FMD) and 1.5-dimensional spectrum was studied. Firstly, through theoretical analysis, pulse energy factor index (PEFI) was designed and used as fitness function. Secondly, RTH algorithm combining with FMD was used to search the key parameters of the optimal decomposition in parallel. Then, the optimal signal component after decomposition was selected by PEFI, and the envelope demodulation was performed. Finally, the 1.5-dimensional spectrum of envelope signal was calculated, and the characteristic frequency information of bearing fault extracted was analyzed in the spectrum diagram to realize the accurate diagnosis of early weak bearing fault. The results of simulated fault experiments and engineering case analysis show that the proposed method can solve the problem of parameter self-adaptation, greatly reducing the impact of noise and other interfering components on diagnosis. It possesses good robustness and can effectively extract weak feature information from early bearing fault signals. It has important practical engineering reference value.

A compressor performance prediction model was proposed for certain sCO₂ coal-fired cycle unit, and the compressor, turbine and boiler models were coupled with the cycle system. Results show that the characteristic sizes and capacity of the compressor follow the 0.5 power law. As the capacity and rated speed increase, the isentropic efficiency improves accordingly. Power consumption is reduced and efficiency is increased when the inlet parameters approach the critical point. When the inlet conditions are fixed, the isentropic efficiency shows a parabolic trend of first increasing and then decreasing with the rise of outlet pressure, with the peak corresponding to the optimal pressure ratio. When the shaft speed of the cycle unit is constant, the thermal efficiency shows a parabolic distribution with the increase of capacity, with the peak appearing at the 300 MW capacity point. If the shaft speed is optimized in coordination with the capacity, the thermal efficiency curve remains parabolic, but the peak shifts to the 600 MW capacity point, due to the weighing effects of turbine efficiency improvement and boiler pressure drop increase.

Based on Aspen Plus software, a carbon capture system model of high-temperature Ca-based adsorbent was established, and simulation study was carried out for CO₂ capture process of flue gas in a 1 000 MW coal-fired unit. Aiming at the problems of high energy consumption and pollutants emission in energy supply of oxygen-enriched coal combustion in calciner, external electric heating energy supply was proposed to provide heat for calciner. The changes in key performance parameters after flue gas entering the carbon capture system were investigated in detail. On this basis, the conservation of energy and mass, as well as the effects of different operating parameters on system performance were analyzed. Results show that after the carbon capture system is added in the 1 000 MW coal-fired generating unit, the thermal efficiency of electricity generation will decrease by 26.11%. When the temperature of the carbonization furnace is maintained at 645 ℃, CO₂ capture efficiency will be 92.13%. CaCO₃ will be decomposed more thoroughly when the calcination furnace temperature is set at 900 ℃. The increase of temperature in carbonation furnace will reduce energy consumption of calcination and improve thermal efficiency of power generation, while the increase of calcination temperature will increase energy consumption and reduce thermal efficiency of power generation. The increase in calcium-carbon molar ratio leads to the increase of solid circulation in the calcium-based carbon capture system, while average carbon conversion of calcium-based adsorbents shows negative correlation.