This paper provides a comprehensive review of the research progress in lignocellulosic biomass pyrolysis technology. The pyrolysis mechanism of various biomass raw materials are summarized, the composition and properties of the products are analyzed, and the regulation, modification and application of the products are reviewed with emphasis. The results indicate that future research directions should focus on the following aspects: technological improvement, committed to improving biomass pyrolysis technology, enhancing energy conversion efficiency and product selectivity; diversification of products, in addition to the main energy products generated by biomass pyrolysis, such as biochar, bio-oil, and biogas, developing high-value chemicals and materials, including bio based chemicals, special chemicals, and high-performance materials should also be focused on; integration with other energy conversion technologies to establish a multi-energy co-supply system by combining biomass pyrolysis with the processes like biomass fermentation, photocatalysis, electrolysis, and energy storage technologies.

Biohydrogen production technologies such as photolysis of water, photo fermentation, dark fermentation, and coupled dark-photo-fermentation were mainly reviewed. The hydrogen production mechanism, technological advantages and disadvantages, influencing factors and research status of each method were analyzed. At the same time, the types and characteristics of biohydrogen production reactors were compared. The results show that biohydrogen production has great potential in low-grade energy treatment and advanced energy production. Finally, some suggestions on the development of biohydrogen production technology were given.

Considering the characteristics of high efficiency and zero carbon emissions of the semi-closed CO₂ cycle, and based on the semi-closed CO₂ power generation system integrated with liquefied natural gas (LNG) cold energy at present, an efficient utilization way of LNG cold energy was proposed. Results show that, for the base case, the energy consumptions of the air separation and compression processes are reduced by 70.4 and 75 MW, respectively, and with a net system efficiency of 63.76%, which is 9.48 percentage points higher than the conventional cycle. Furthermore, with optimization measures such as improving the system parameters and matching the heat capacities of regenerators, the net efficiency of the optimized case is further increased to 72.22%, and the exergy efficiency is 51.27%. Compared with the reference system Ⅱ of only integrating LNG cold energy within the power cycle, the exergy efficiency of cold energy utilization is improved by 28 percentage points.

In response to the challenges faced in the digital and intelligent operation and maintenance (O&M) of wind turbines, such as data overload of multiple units, information redundancy, low efficiency in maintenance knowledge retrieval and insufficient reasoning of life-cycle maintenance knowledge, a knowledge graph construction method for wind turbine operation and maintenance data was proposed. Firstly, important information such as faulty components and causes could be extracted using text data such as wind turbine equipment maintenance work orders, so as to provide the knowledge graph construction process for wind turbine operation and maintenance data.Subsequently, during the construction process, modeling analysis was conducted specifically for fault entities, attribute extraction and relationship extraction. Results show that the wind turbine O&M knowledge graph helps O&M personnel to accurately grasp the root causes of failures, efficiently implement maintenance measures, and ensure the repair capabilities of wind turbines under the conditions of informatization and intelligence. Moreover, compared to relational databases, the proposed design method offers better performance in terms of query precision and time.

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.

The effect of channel height on the thermal-hydraulic performance of airfoil fin printed circuit heat exchangers(PCHEs) was investigated by numerical method based on the impact of channel geometry. Results show that channel height significantly affects the compactness, resistance, and heat transfer performance of PCHE. Under the same Reynolds number (Re=6 000-14 000), the Fanning friction factor f first decreases and then increasesas with the channel height H decreases (i.e., the ratio of channel height to transverse pitch H/S_T=0.12-0.60), with the lowest f observed at H/S_T=0.24. The Colburn-j factor j shows no significant change for airfoil fin channels with H/S_T=0.24-0.60, while an increase in j is observed at H/S_T=0.12. The ratio j/f is suitable for evaluating the comprehensive performance of airfoil fin channels with different heights. When using j/f as the comprehensive performance evaluation indicator, the airfoil fin channel with H/S_T=0.24 exhibits the best overall performance.

A covert attack method based on a symbiotic organism search(SOS) algorithm to optimize long short-term memory (LSTM) neural network was proposed to solve the problem of obtaining a high-precision estimation model of the attacked target for covert attacks. The output and input signals of the feedback controller of the attack target were taken as the data set of the LSTM. The estimation model of the attacked area was obtained through training, and was used to design the covert attacker to impose attack signals on the attacked object.In addition, the SOS algorithm was applied to optimize the parameters of the LSTM to improve the performance of the covert attacker.The simulation results of covert attack on the primary circuit control system of nuclear power plant show that the attack method has high concealment performance while realizing preset attack behavior on the output signal of the target control system.

A cooperative control strategy of deep deterministic policy gradient (DDPG) and proportion integration differentiation(PID) based on multidimensional state information and segmental reward function optimization was proposed for the selective catalytic reduction(SCR) denitrification system with large inertia and multi-disturbance. Addressing the problem of low strategy learning efficiency of the DDPG algorithm caused by the partially observable Markov decision process (POMDP) in the SCR denitrification system, the multidimensional state information of the SCR denitrification system was designed firstly. Secondly, the segmented reward function of the SCR denitrification system was designed. Finally, a DDPG-PID cooperative control strategy was designed to achieve the control of SCR denitrification system. Results show that the designed DDPG-PID cooperative control strategy improves the strategy learning efficiency of the DDPG algorithm and the control effect of PID. Meanwhile, the designed cooperative control strategy has strong set value tracking capability, anti-interference capability and robustness.

In order to reduce the influence of solar energy fluctuation on the performances of the solar-coal complementary power generation system, a new type of solar-coal complementary power generation system was proposed. Models of key devices and subsystems were developed and verified, and the thermal and techno-economic performances of the new solar-coal complementary power generation system were studied. Results show that the thermal performance of the system decreases with the operation load, and increases firstly and then decreases with the increase of direct normal irradiance. The average annual output power of the system is 699 MW, the average annual coal saving rate is 7.506 g/(kW·h), and the average annual solar-to-power efficiency is 10.82%. When the heat storage capacity duration is 10 h, the system has the best techno-economic performances, with the life-cycle net present value of 4.18×10⁸ yuan, the internal return rate of 11.81% and the dynamic payback period of 12.6 years. The levelized cost of electricity is 0.402 yuan/(kW·h), and the profitability is good.

To solve the issue of un-stable operation of thermal power units caused by severe fluctuations in the power grid, a secondary frequency regulation control strategy assisted by flywheel energy storage considering the operation stability of thermal power plant was proposed. Firstly, a secondary frequency regulation control model for ultra-supercritical thermal power units integrated with the flywheel energy storage was developed. Then, a non-linear decomposition method for AGC instructions based on constraints of multi-layer variable gain rates was proposed. Finally, a fitness function was designed based on the unit stability and the AGC performance of the system, and the whale optimization algorithm (WOA) was used to obtain the optimal parameters of limiting algorithm. Based on the above method, a collaborative control strategy of secondary frequency regulation was designed for the integrated system of thermal power unit and energy storage. A simulation verification was conducted on the integrated system with a 1 000 MW thermal power unit and flywheel energy storage as an example. The results show that the proposed control strategy can effectively respond to high-frequency commands of the integrated system without affecting the frequency regulation performance, reduce the action amplitude of thermal power unit, and improve the stability of power unit operation.

To explore the effect of biomass components such as cellulose, hemicellulose and lignin on physical properties of pellets, cotton stalk and wood sawdust were mixed with their components at different mass ratios to prepare the pellets. The apparent density and compressive strength of pellets were analyzed by electronic universal material testing machine. The biomass molecular structure before and after briquetting was analyzed by X-ray photoelectron spectroscopy. Results show that the compressive strength of pellets is directly affected by cellulose, meanwhile hemicellulose and lignin mainly act as binders to improve the compressive strength of pellets indirectly. The addition of cellulose or hemicellulose to cotton stalk significantly increases the C—OH functional group in its pellets, and C＝C functional group is formed, which are conducive to form the intermolecular force and increase the stability of molecular structure. They can enhance the physical properties of pellets.

To enhance the quality of biomass gasification products, briquettes of eucalyptus bark and corn stalk were used as the typical feedstocks for the fluidized bed gasification experiments. Rice husks and sawdust were selected for comparison. Gasification experiments were conducted on a pilot-scale fluidized bed to obtain the optimal air equivalence ratio values for rice husks, sawdust, and the briquettes of eucalyptus bark and corn stalk. The causes of slagging during biomass briquettes gasification were analyzed. Results show that the optimal air equivalence ratio value for briquettes of eucalyptus bark, rice husks and sawdust is 0.20, and the gas heating values of the three biomass are 5.5 MJ/m³, 5.5 MJ/m³ and 6 MJ/m³ respectively, the corresponding gasification efficiencies are 60%, 45% and 52%. While the optimal air equivalence ratio value of corn stalk briquette is 0.24, which means requiring more air due to the high ash content and low heating value. The gas heating value of corn stalk briquettes is 4 MJ/m³, and the gasification efficiency is 35%. The increase in gasification temperature promotes the gasification reaction of various biomass. Biomass briquettes with high concentration of alkali and alkaline earth metals are more susceptible to slagging during gasification.

Optimization research was conducted on supercritical carbon dioxide recompression cycle system applied to the fourth generation gas-cooled reactor. By establishing a comprehensive thermodynamic and exergoeconomic model, and introducing spatial compactness indicators based on the demand for nuclear power modularization, a study was conducted on supercritical carbon dioxide recompression cycle system from multiple dimensions such as thermodynamic performance, spatial compactness, and exergoeconomic performance. Impact of key parameters on the performance of supercritical carbon dioxide recompression cycle system was analyzed, and further multi-objective optimization was carried out to improve the applicability of the system. Results show that through multi-objective optimization, the comprehensive performance of the cycle is improved, and the optimal exergy efficiency, unit power cost rate, and required heat exchange area per unit output power are 71.5%, 3.11 cent/(kW·h), and 0.191 m²/kW, respectively.

Large-scale grate furnaces have been widely used in the energy conversion of biomass and municipal solid wastes (MSW). However, due to the fact that design and operation of grate furnaces are still in the stage of engineering exploration, in the actual operation process, there are still problems such as high excessive air rate, poor combustion efficiency in both gas and solid phase, and high initial NO_x emissions. In response to the complex layered combustion process of grate furnaces, a large-particle conversion model and a multi-component parallel particle combustion model were constructed to achieve fine numerical simulation of actual grate furnace combustion processes. The accuracy of this model was verified by comparing with experimental results. Using numerical simulation methods, real-furnace analysis and optimization were carried out for large-scale grate furnaces burning MSW and agricultural straw. Based on the surface- and bottom-ignition modes, on-site adjustments were made. Results show that for the middle-arch SW incinerator, localized high temperature and high NO_x emission are mainly caused by the departure of component distribution, combustion and reduction reactions from design, which are clearly improved by the operation adjustment. According to numerical modeling calculation, a further optimization in its structure can reduce NO_x emission to 26.8 mg/m³. For the vibrating grate boiler for straw, low combustion efficiency in gas and solid phase is mainly caused by the convective cooling of large primary air and the "chimney-like flow" in furnace. After optimization, its emission is hugely reduced, and power-generation load remarkably rises.

Ammonia-coal co-firing involves complex chemical reaction processes, and it is highly concerned that whether co-firing exacerbates the generation of nitrogen oxides. Using the method of chemical reaction kinetics calculation, the reaction pathways of NO generation and reduction in the gas-phase reaction of ammonia-coal co-firing were studied, as well as the effects of different factors on NO generation. Results show that compared to pure coal combustion, the NO volume fraction at the outlet of the reactor can be reduced by 96.5% with the ammonia co-firing ratio of 0.3 at temperature (T) of 1 300 ℃ and excess air coefficient (α) of 0.84. Since ammonia decomposition generates a large number of free radicals such as NH₂ and NH, which leads to a faster reduction reaction rate and the conversion of N-containing elements into N₂ under co-firing working condition. At T=1 300 ℃, an ammonia co-firing ratio of 0.3 is suitable, since the volume fractions of NO and NH₃ at the reactor outlet are both low. Small ammonia co-firing ratio will increase the rate of NO generation and NH₃ decomposition, leading to an increase in NO volume fractions at the reactor outlet. The higher the temperature is, the more obvious this phenomenon is. Reducing atmosphere (α<1) and a lower temperature (T≤ 1 300 ℃) can effectively reduce NO emissions.

Machine learning methods have demonstrated promising applications in biomass gasification modeling. However, machine learning models primarily rely on experimental data and do not consider the reaction mechanisms in gasification. In situations that data samples are insufficient, there can be significant deviations between the actual correlation characteristics exhibited by the model and the mechanistic laws. Thus a method for predicting biomass gasification product distribution based on physics-informed neural networks (PINN) was proposed. This method seamlessly integrated real experimental data with prior mechanistic knowledge, embedding boundary constraints and monotonic relationships among key parameters into the artificial neural network(ANN) model. Automatic differentiation techniques were used to assist optimization, enabling efficient model training. Results show that the PINN model achieves a coefficient of determination greater than 0.89 and a root mean square error less than 4%, the overall prediction accuracy is superior compared to the three models which are purely fitting based on machine learning: random forest (RF), support vector machine (SVM) and ANN. Furthermore, the PINN model strictly adheres to boundary constraints and prior mechanistic monotonic relationship, exhibiting better interpretability and generalization capabilities.

To solve the problems of inadequate cyclic stability, low thermal conductivity, and insufficient light absorption in CaO/CaCO₃ energy storage system, discussions were conducted on improvement methods for the performance of calcium-based materials from the aspects of the selection of calcium-based raw materials, addition of doping elements in composite materials, and adjustment of operating conditions. Results show that inert oxides are formed within materials through the addition of elements such as Al, Mn, and Ti, which can inhibit sintering and further improve the cyclic stability of materials. The thermal conductivity of materials can be enhanced by the doping of materials with high thermal conductivity, such as Al₂O₃, MgO, SiO₂, and ZnO. Additionally, the spectral absorption of materials can be improved by the doping of elements such as Mn, Cu, Fe, Co, and Cr. Corresponding summaries may provide a reference for the design of materials for thermochemical energy storage.

In order to solve the problems of instability and utilization of renewable energy, a combined cooling, heating, and power (CCHP) system was proposed that integrated solar photovoltaic/thermal, water electrolysis for hydrogen production, and biomass gasification and methanation. Aiming at the capacity matching problem of the CCHP system under high dimensional target, an improved beluga whale (MOBWO) algorithm was proposed and verified. The proposed algorithm improved the distribution of solutions and the convergence rate. A case study based on this method shows that compared with the individual systems, the fossil fuel consumption is reduced by 56.8%, the CO₂ emission is reduced by 53.1%, and the flexibility reaches 51.6%, although the annual total cost of the optimal capacity allocation scheme is increased by 19.8%. In this case model, the MOBWO algorithm has better solving performance than non-dominated sorting genetic algorithm-II (NSGA-2) and multi-objective particle swarm optimization (MOPSO) algorithm.

By dividing the incident solar spectrum into bands, an integrated photovoltaic (PV) and photothermal (PT) driven organic Rankine cycle (ORC) was established. Thermodynamic analysis of the system was conducted under the temperature limit of 100 ℃ for the cooling panel, to identify suitable working fluids for the ORC system and optimize the evaporation temperature. Results show that isobutene as the cooling fluid for the photovoltaic system and the working fluid for the ORC system, the highest system efficiency can be achieved. Frequency division technology transfers the heat dissipation load of the cooling panel to the collector, which can reduce the cooling demand of the photovoltaic panel and thus reduce the mass flow rate of the working fluid. It has a positive effect on improving the system's power generation capacity, and can enhance the efficiency of pure photovoltaic electricity generation by 9%. Additionally, frequency division efficiency and the absorption band of solar cells significantly impact the overall efficiency of the integrated power supply system.

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.

Severe ash deposition and slagging issues have occurred during the combustion utilization of Xinjiang coal, and adding kaolin additives is an effective way to address these issues. With the sedimentation furnace ash accumulation experiments and the fixed-bed sintering experiments, the performances and mechanism for prevention and control of kaolin with different particle sizes were studied. Results show that kaolin changes the ash-forming characteristics of Xinjiang coal through its dilution and interaction with minerals in coal, which in turn affects the ash accumulation behaviors and sintering characteristics. Although fine kaolin can effectively inhibit the vapor deposition of alkaline substances through interaction, the dilution of the additives leads to a smaller ash particle size. Therefore, it is easier to form ash deposition in the initial stage. Under the combined effect of above two aspects, fine kaolin and coarse kaolin have similar prevention and control effects on the growth of ash accumulation in the initial stage. In addition, the smaller ash size distribution after the addition of fine kaolin promotes the development of ash sintering degree, which is not conducive to the soot blowing and removal of sediments.

Using splitter blades can effectively improve flow blocking problem in blade channel and reduce flow loss. Aiming at an ORC radial inflow turbine with certain splitter blades, the influence of different splitter blade lengths and circumferential offset on turbine performance was studied. And internal flow conditions, blade load and loss distribution were analyzed by numerical simulation of different blade layout schemes. Results show that the splitter blade can effectively weaken the vortex in the channel, improve the flow condition, and make the pressure distribution inside the channel reasonable. At the same time,it can share part load of the main blade to a certain extent. Compared with the length of the splitter blade, the influence of circumferential offset on the distribution of entropy yield is obvious. With the increase of length and circumferential offset, the high entropy yield range and total pressure loss coefficient show a trend of first decreasing and then increasing, and the change of isentropic efficiency is the opposite. When l=0.5 and d=0.5, the isentropic efficiency is the largest by 91.26%, and the power is roughly positively correlated with blade length. When the length coefficient and circumferential offset are controlled between 0.5-0.6, the ideal flow condition and blade load distribution can be maintained, and the high entropy yield range is small, which is conducive to the improvement of turbine performance.

In order to alleviate the extensive energy consumption of amine-based carbon capture, nanoscale aluminum oxyhydroxide was applied as the catalyst to reduce the heat duty of amine regeneration. The desorption process was divided into a heating-up stage and an isothermal stage based on the basic heat transfer theory. An energy consumption assessment model for calculating the heat input during different stages was established, and the real-time heat duty variation curves were obtained. This model was more precise than conventional methods, and was beneficial for determining the optimal operation conditions to reach the lowest energy consumption. Based on this method, the best desorption temperatures to achieve the lowest heat duty with and without catalyst were investigated. Results show that moderate temperatures can bring the lowest energy consumption. Besides, through the analysis of the overall reaction kinetics during the regeneration process, it is found that the reaction order model is most suitable for describing the reaction rate of ethanolamine solution. The parameters of the reaction order model prove that the catalyst saves the energy consumption of regeneration by reducing the activation energy of the desorption reaction.

In order to study the SO₃ generation characteristics of SCR system during low temperature operation, the effects of flue gas temperature, SO₂ mass concentration and ammonia injection on the catalytic SO₃ generation characteristics were analyzed on a pilot test bench. Results show that temperature is the main factor affecting the SO₃ generation rate. SO₃ generation rate decreases as the flue gas temperature decreases,which is also influenced by SO₂ mass concentration. However, the effect of SO₂ mass concentration on SO₃ generation rate becomes very little when the inlet flue gas SO₂ concentration is in the range of 700 to 1 150 mg/m³ and temperature is below 260 °C. Compared with the un-injected ammonia condition, both the outlet SO₃ mass concentration and SO₃ generation rate decrease under ammonia injection condition. At the same time, the probability of low-temperature corrosion decreases, and the probability of ammonium bisulfate generation increases. Since SO₃ generation rate in the SCR system decreases at low temperature, the harm to the low-temperature heating surface is reflected in the low-temperature corrosion and blockage under the synergistic effect of H₂SO₄ and ammonium bisulfate.

Vacuum gas nitriding process was applied to strengthen the surface of the SP-700 titanium alloy at different temperatures. The surface morphology, cross-sectional morphology, hardness, abrasion resistance and electrochemical corrosion performance of the newly formed gas-nitrided layers were investigated using scanning electron microscope (SEM), optical microscope (OM), micro-Vickers hardness tester, reciprocating friction and warm damage tester, white light interference three-dimensional surface profiler and electrochemical workstation, respectively. The corrosion behavior of the gas-nitrided layers was determined by immersion corrosion method in HF solution. Results show that, the microstructural morphologies of the gas-nitrided layers are significantly influenced by the processing temperatures. With the increase of temperature, the amount of nitride increases and the nitride layer becomes denser. The hardness of the high-temperature gas-nitrided layer was about 1.9 times higher than that of the matrix, and the relative abrasion resistance can reach 51.34. All samples can be passivated spontaneously in 3.5% NaCl solution, indicating their good electrochemical corrosion resistance. The samples with gas-nitrided layer perform better in HF corrosion solution, and the higher the processing temperature, the better the corrosion resistance of the samples.

Heat generated during the incineration of hazardous waste is usually used to produce saturated steam to supply steam, heat and other needs for industrial parks, which can also be used for low-temperature power generation. The thermodynamic performance of the saturated steam-driven organic Rankine cycle (ORC) system was analyzed. Based on thermal matching analysis of the steam latent heat source and the ORC system under the basic working condition, three optimization measures were proposed, and the thermodynamic performances of the system with single optimization or combined optimization measures under different working conditions were studied. Results show that the combined optimization method can make the system achieve better performance, and the maximum net output work is 3 193.81 kW, which is increased by 170.46% compared with the basic working condition. Accordingly, the thermal efficiency is 23.34% with an increase of 30.25%, and the total exergy efficiency is 66.25% with an increase of 41.80%.

In the face of the increasingly urgent need for the reduction of carbon emission and energy consumption, the development of efficient advanced thermal cycles with low carbon emission is becoming more and more important. A natural gas fueled semi-closed supercritical CO₂ cycle was proposed with zero carbon emission, and the semi-closed cycle was split into an open cycle and a closed cycle through working fluid splitting to further clarify the thermal to power conversion process. Furthermore, the cycle splitting method was applied to the complex modified cycle, which was split into several simple cycles to formulate the thermodynamic evaluation models of the different process modification measures and intuitively reveal the energy-saving mechanism of different cycle configurations. Through parameter sensitivity analysis, the optimum parameters of process modification measures were obtained. Results show that the cycle efficiency can be effectively improved by various cycle layout modification measures such as reheating, recompression, intermediate cooling and partial cooling, which can contribute to the efficiency improvement of 1.79~5.59 percentage points. After the integration and optimization of various process modification measures, the net power generation efficiency of the system is increased by 10.18 percentage points compared with the basic cycle.

In order to realize stable, efficient and environmentally friendly coordination of waste incinerator power generation units, multi-objective optimization was conducted for combustion process of the incinerator. A dynamic modeling method combining extreme learning machine (ELM) and nonlinear autoregressive moving average model with exogenous inputs (NARMAX) was proposed, and the parameters of the model are optimized by improved sparrow algorithm (ISSA). The dynamic models of steam flow, boiler efficiency and first flue temperature of the incinerator were established respectively. The ISSA-ELM-NARMAX model was compared with the traditional BP neural network model, ELM-NARMAX model and SSA-ELM-NARMAX model. Finally, multi-objective optimization of the combustion process was carried out to find the optimal operating parameters of the incinerator based on the improved non-dominated sorting genetic algorithm (NSGA-II). Results show that the dynamic model of combustion process of the incinerator based on ISSA-ELM-NARMAX is more accurate and effective, and the proposed control strategy can provide operational guidance for the incinerator operators.

Aiming at the measurement problem of gland seal leakage of high pressure (HP) and intermedia (IP) combined turbine, a method of determining the gland seal leakage by introducing intermediate variable was proposed. And a calculation method was derived through theoretical analysis. The total amount of gland seal leakage of HP and the component of IP side gland seal leakage at different conditions were calculated by taking the leakage of IP balance piping of gland leakage as an intermediate variable. Taking a subcritical 600 MW steam turbine as an example, the calculation results were compared with the design conditions. Results show that the relative error of gland seal leakage is within 1%. Compared with the calculated values by the variable steam temperature method, the relative error of the IP side gland seal leakage is within 5%. Research results prove that the proposed method is reliable in theory and has high accuracy in calculation, also simple in operation and feasibility.

Based on the conventional medical waste gasification polygeneration system (conventional scheme), two low-carbon schemes 1 and 2 coupled with carbon capture and storage (CCS) were proposed. The three schemes were compared from the viewpoints of energy, exergy and economy (3E). The exergy analysis of optimal scheme 2 was carried out, and the impact of exhausted gas recirculation (EGR) on system performance was discussed. Results show that the overall exergy efficiency of scheme 2 is increased by 7.18% with 15.38% reduction in net power generation efficiency compared with conventional scheme. The dynamic payback period (DPP) of low carbon scheme 2 is 3.12 years less than that of scheme 1, and the net present value (NPV) is increased by 5.906 0 million yuan. Scheme 2 can ensure the excellent performance of the system and achieve the goal of low carbon emissions with significant economic benefits. Meanwhile, increasing the exhausted gas recirculation ratio can enhance the economic benefits of the integrated system.

To further improve the aerodynamic performance of airfoils, a bionic curved flap was proposed based on the trail fin profile of mako sharks. The aerodynamic performance and internal flow of the bionic airfoil were simulated using the SST k-ω turbulence model, and the effects of relative position and installation angle of the bionic flap were analyzed to obtain the optimal bionic flap airfoil with the best aerodynamics, which was compared to the Gurney flaps. Results show that after installing a bionic flap, its lift-drag ratio is significantly higher than the baseline; when the relative flap height remains unchanged, reducing the installation angle and increasing the distance between the flap and the trailing edge lead to an early airfoil stall onset. The aerodynamic performance of the bionic flap airfoil with reverse installation angle of 45° at the trailing edge is the best, and the lift coefficient is 5.9% higher than the Gurney flap airfoil before the stall. After arranging the bionic flap, the flow field tends to be complicated, and the position, quantity and size of vortices change.

A fault warning method based on the improved whale algorithm to optimize the hyperparameters of Transformer network (IWOA-Transformer) was proposed. The method improved the whale optimization algorithm (WOA) by utilizing nonlinear convergence coefficients and Gaussian variation to improve its convergence speed and avoided falling into local optimum. Then, the hyperparameters of Transformer were optimized with the improved whale optimization algorithm (IWOA) to establish a fault warning model of coal mill, and the adaptive threshold was determined by the similarity function of predicted and actual values. Combined with the expert system, the fault type was judged and solutions were proposed,and coal mill fault early warning was achieved. Finally, A fault warning test was conducted using a 350 MW cogeneration unit medium-speed coal mill as an example. Results show that the IWOA-Transformer model can significantly improve the speed and accuracy of early warning, and has practical engineering value.

Using thermogravimetric (TG) technique and inductively coupled plasma emission spectrometer (ICP-OES), the combustion characteristics of individual straw and coal gangue and their co-combustion characteristics, the retention characteristics of alkali metal elements in straw were investigated, and the kinetic characteristics of the co-combustion process of straw and coal gangue were analyzed using the Coats-Redfern integral method. Results show that in the co-combustion process of straw and gangue, there is a strong interaction, in which the best combustion characteristics are achieved with the gangue mixing ratio of 10%. With the increase of coal gangue addition, the combustion reaction activation energy of the fixed carbon in the mixtures decreases and the interaction gives rise to a change of reaction mechanism in the combustion process; the best inhibition effect for the release of alkali metals is attained with the gangue mass fraction of 10%, meantime the best retention effect of alkali metals K and Na is also attained at 1 000 ℃ and 1 100 ℃, respectively.

To explore the application potential of sound-assisted combustion technology in W-shaped flame boilers, the combustion characteristics of a W-shaped flame boiler with real-time load of 315 MW under acoustic excitation were experimentally studied. Twelve and four acoustic excitation devices were staggered in the main combustion area and the burning area of the boiler, respectively, and they were put into operation in a group of three devices in a circular manner. The frequency of the motor driving the acoustic excitation device was 35 Hz, and the corresponding intake pressure was maintained at 0.35-0.47 MPa. In the test, the changes of the NO_x mass concentration at the inlet of the A and B sides of the denitration tower, the SO_x mass concentration at the inlet of the desulfurization unit, and the coal consumption of the unit were recorded through the distributed control system (DCS) of the centralized control room of the power plant. Results showed that, after the acoustic excitation was put into the denitrification tower, the mass concentration of NO_x at the inlet of the A and B sides of the denitration tower is decreased by 6.08% and 5.47%, respectively, the SO_x mass concentration is decreased by 1.24%, and the average coal consumption of the unit is decreased by 1.5 g/(kW·h). In addition, based on the ash sampling analysis of the economizer and air preheater outlet, it is found that the carbon mass fraction of fly ash is decreased by 1.64% and 1.70% respectively, compared with the case without acoustic excitation. Sound-assisted combustion technology can effectively improve the thermal efficiency of W-shaped flame boilers and reduce pollutant emissions.

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.

To control plumes and save water resources, a hot test system for high level water collection mechanical cooling tower was established for comparative analysis of the plume abatement, water saving and thermal performance of the external cooling module (dry-wet hybrid cooling tower) and the internal condensation module (condensation plume cooling tower). The impact of the ambient temperature, inlet circulating water temperature and circulating water flow rate on the performance of cooling towers was studied. Results show that dry-wet hybrid cooling tower and condensation plume cooling tower have plume abatement and water saving capabilities, which are achieved at the cost of cooling performance reduction of the cooling tower. Compared with the original tower, the circulating water temperature drop of dry-wet hybrid cooling tower and condensation plume cooling tower decreases by about 1.5 K. The plume abatement and water saving performance of the dry-wet hybrid cooling tower and the condensation plume cooling tower is greatly affected by the operating parameters, and the water saving amount and water saving rate of the condensation plume cooling tower are higher than those of the dry-wet hybrid cooling tower.

A model-data joint prediction method was proposed. The object dynamic model was established through mechanism analysis, and the future solar radiation intensity and user load prediction data were introduced for immediate model prediction. The data prediction model was established through the convolution - short and long time memory hybrid neural network improved by attention mechanism, and the historical data was introduced for rolling data prediction. Then, Kalman filter was used to combine the output of the two prediction models to realize the joint prediction of energy storage. Results show that the combined prediction has the advantages of both methods, which can solve the problem of accumulated energy storage prediction errors over time and timely characterize the changes of energy storage when meteorological factors suddenly change and system operation mode changes. The proposed method has good prediction accuracy under various weather conditions.

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.

This paper proposed an integrated system which includes a tower-type solar thermal power system and energy storage system, employing S-CO₂ and quartz as the storage media and a re-compressed S-CO₂ Brayton cycle as the power cycle. Based on the Gensystem platform, mathematical models of the power cycle, solar heat collection system, and S-CO₂ thermocline storage tank were developed to investigate the performance of the heat collection system and the dynamic characteristics of heat storage and release in the S-CO₂ thermocline storage tank. This foundation facilitated an analysis of the integrated system's thermodynamic and economic performance. Results show that after 13 cycles of heat storage and release, the temperature at the outlet of the thermocline storage tank tends to be stable. At the conclusion of heat release, the temperature of the thermal fluid exiting the tank is decreased by 63 K, while at the end of heat storage, the temperature of the cold fluid exiting is increased by 46 K. Compared with a dual storage tank tower solar thermal power system, the average daily power generation efficiency on the summer solstice and winter solstice is enhanced by 1.8% and 1.7%, respectively. The total system investment is reduced by 9.46%, the levelized cost of electricity is reduced by 9.45%, and the investment payback period is shortened by 1.8 years.