Tibet is located in the hinterland of the Qinghai-Tibet Plateau, the area above 4 000 m accounts for 85% of the total area of the region, its geothermal resources are very rich. To realize the reasonable exploitation of geothermal resources, combined with the carbon peaking and carbon neutrality strategy, the current situation of the development and utilization of geothermal resources in Tibet is comprehensively combed, and the suggestions for the future development of the geothermal industry are put forward. The analysis shows that the geothermal resources of hydrothermal and dry hot rock in Tibet have large storage capacity, good quality, and excellent power generation potential. The shallow geothermal resources are mainly distributed in Lhasa, which can be combined with heat pump technology for local heating. At present, there are still some problems in geological exploration, technical improvement, equipment development, and operation management. It is necessary to develop ORC units, build EGS experimental platform, and scientifically develop deep geothermal energy. The research shows that the development and utilization of geothermal resources in Tibet should follow the principles of "survey-based, power generation-based, heating-assisted, equipment upgrading, and cascade utilization", promote the scientific exploitation and efficient utilization of geothermal resources, improve the geothermal industry chain, and effectively improve the energy consumption structure in Tibet.

With the completion of ultra-low emission transformation of thermal power plants, problems such as increased costs and excessive ammonia injection have arisen. Modeling and optimization of power plant operation data through machine learning has become an important means to solve the above problems. This article reviews the commonly used machine learning algorithms and their application scenarios in reducing nitrogen oxides. In terms of algorithm, the main algorithms of data preprocessing, modeling prediction and parameter optimization and their applicability to nitrogen oxides removal are summarized. The research directions of multi-operating condition data preprocessing method and the construction method of the objective function in multi-objective optimization are proposed. For the application level of the machine learning methods, such as low nitrogen combustion in the furnace, optimization of SCR denitration system, and comprehensive energy saving and consumption reduction of the whole system, the implementation methods and corresponding effects are summarized. The future research directions of long-period dynamic modeling control and multi-power plant joint modeling have prospected.

In order to build a new power system with new energy as the main body, thermal power unit should undertake the new task of flexible operation and deep peak-regulating while maintaining power and heating supply. However, the conventional detection and communication technology is limited by the problems of poor real-time performance, slow transmission and high investment, which is difficult to support the new demand of thermal power units. Advanced detection technology and communication technology represented by 5G provide solid technical support for the state research, judgment and operation adjustment of thermal power units represented by boiler system by building a complete perceptual transmission chain, but they also face problems such as high construction investment, lack of professionals and standards. Only by setting out from the actual production, perfecting the mechanism and changing the concept, can the application effect of advanced detection and communication technology be realized. As an important part of smart power plant, the advanced detection and 5G technology will provide a solid foundation for improving the overall intelligent level of thermal power generation.

Micro-mixing combustion is a kind of potential technology to reduce pollutant emissions, and the microtube structure as a basic unit has significant influence on combustion characteristics. Taking the single microtube model burner as the object, the computational fluid dynamics (CFD) method is employed to analyze methane micro-mixing combustion characteristics with different microtube diameters, rear-section lengths, and chamber-to-tube area ratios, under the air-preheated and pressurized condition and the atmospheric condition. The numerical simulation results show that, the flame length increases obviously under the atmospheric condition, and the increase rate is greatly affected by the microtube diameter and the area ratio. With the increase of microtube diameter, the flow and temperature fields in the flame chamber are similar, and the dimensionless flame length does not change significantly. However, when the microtube diameter is smaller, the change of flame length is smaller between two working conditions, and the flexibility is better. With the increase of microtube rear-section length, the turbulence intensity at the microtube outlet reduces greatly, and the flame length increases obviously, but the change trend of flame length is consistent under two working conditions. With the increase of chamber-to-tube area ratio, the flame length decreases at first and then increases. When the area ratio is 4.0~9.0, the flame length is relatively short, and the combustion performance is relatively good. The results have reference value for the gas turbine combustor, and also have certain reference significance for free jet flame.

With the proposal of "carbon peaking and carbon neutral", the total installed capacity of renewable energy power units continues to increase. This may greatly challenge the safety and stability of power grid. The characteristics of flywheel energy storage system (FESS) are fast response, unlimited times of charge and discharge and deep depth of discharge. FESS has been widely used in frequency modulation and frequency safety improvement of power grid. In order to make full use of the advantage of flywheel energy storage in auxiliary frequency modulation of the power grid, an adaptive coordinated droop control strategy of primary frequency regulation coordinated with thermal power units was designed, which realized the power cooperative adaptive adjustment of the combined coal-fired thermal power units and storage systems. Simulation results show that, the proposed control strategy can effectively improve the frequency modulation performance of the combined fire-storage system. Compared with the conventional droop control, the maximum dynamic frequency difference and steady frequency difference of the system reduces by 29.00% and 25.50% respectively, which eases the frequency modulation pressure of thermal power unit, and is benefit to safety and stability of the thermal power unit.

In order to improve the energy utilization efficiency of high flexibility power generation system coupled with internal combustion engine and coal-fired unit, a new thermal system combined with the internal combustion engine and the coal-fired unit was proposed. By feeding the flue gas of internal combustion engine and the waste heat of cooling water into the thermal system of coal-fired generating unit, the coal consumption of coal-fired generating unit can be reduced. EBSILON software was used to model the composite system. Steam consumption rate and heat consumption rate of the coal-fired units were taken as evaluation indexes to analyze the thermal economy of the coal-fired unit under different composite schemes. The results show that, the heat consumption rate and steam consumption rate of the coal-fired unit can be significantly reduced by combining the waste heat of the internal combustion engine into the thermal system of the coal-fired unit. The closer the compound position of flue gas waste heat is to the boiler, the smaller the proportion of feed water and condensed water involved in flue gas heat exchange, and the lower the heat consumption rate and steam consumption rate of the unit. When one part of the flue gas waste heat is used to heat the high pressure heater feed water and the other part is used to heat the low pressure heater condensed water, more waste heat will be allocated to feed water, and the heat consumption rate and steam consumption rate of the unit wil decrease. After optimization, the heat consumption rate of the combustion engine and coal-fired unit combined thermal system can be reduced by 6.62% at most.

An efficient integrated power generation system of solid waste coupled with anaerobic fermentation and incineration is proposed. Solid waste anaerobic fermentation is adopted to generate biogas, which enters the biogas burner to burn and generates high-temperature flue gas, and the flue gas heats the steam-water system and the primary and secondary air through the heater and air preheater in the unit. Under the condition that the heat generated by solid waste incineration in the boiler is not changed, the energy entering the steam turbine to do work is increased, thus the power generation efficiency of the whole unit increases. At the same time, according to the first law of thermodynamics and the second law of thermodynamics, the reasons for power generation efficiency and exergy efficiency improvement are analyzed. The results show that, compared with the case unit, the proposed high-temperature flue gas system with biogas combustion can increase the net power generation by 8.69 MW. In addition, the power generation efficiency and power generation exergy efficiency of the new system has increased by 3.56 percentage points and 9.74 percentage points, respectively. Economic analysis shows that the proposed coupling system is equipped with an anaerobic fermentation biogas combustion system, and the dynamic recovery period is 3.78 years, which has obvious economic advantages.

The variable operating condition of thermal power units makes the data show multi-modal characteristics, which leads to the decrease of prediction accuracy of the regression soft sensor model based on shallow network structure. An improved BP neural network (back propagation neural network, BPNN) soft sensor method is studied. Firstly, the original data features are extracted by using the strong deep learning ability of stacked sparse autoencoder (SSAE), and then the extracted features are analyzed by BPNN. The experimental results show that, the mean square error of the SSAE+BPNN soft sensor method is 0.135 8×10^–3 and the square correlation coefficient is 0.983 2. It is proved that its prediction accuracy and generalization ability are significantly better than those of BPNN. It is applied to the soft sensor of carbon content in fly ash of a flexible peak-shaving 660 MW ultra-supercritical generator set, and the average relative error of the prediction results is 0.91%, the overall relative error is less than±5%, indicating the method has good engineering application value.

By taking a supercritical 600 MW opposed firing boiler as the research object, the temperature deviation law of main steam on both sides is analyzed and verified through hydrodynamic modeling, and a technical scheme is put forward to optimize the temperature deviation of main steam from the perspective of water side. After adopting this steam temperature optimization scheme, the main steam temperature deviations on both sides of the boiler reduced by 44.6%, 95.8% and 28.0% respectively under 50%, 75% and 100% BRL conditions. This scheme can realize safe and economical operation of the unit, and has good guidance and reference value for the same type of boiler.

With high power generation efficiency and low carbon emission, (ultra) supercritical unit is the main type in China's development of thermal power units. Optimization on feed water operating condition of the (ultra) supercritical unit is of great guiding significance. The optimal control indexes of different feed water operating conditions of (ultra) supercritical units are investigated by in-situ sampling test, and the influence of centralized sampling on feed water quality is researched. Moreover, the intelligent control system for feed water operating condition is developed. The results show that, the optimal target value of feed water conductivity is 6.7 μS/cm under AVT(O) condition, the optimal target value of feed water dissolved oxygen is 15 μg/L and the optimal target value of feed water conductivity is 3.0 μS/cm under OT condition. Long sampling pipeline of feed water will cause the deposition of iron corrosion products, and interfere with the judgment of unit corrosion. The chromates produced by adding oxygen to feed water is only related to the oxidation of the sampling tube and has nothing to do with the water vapor system.

In the point cloud splicing of underground pipe gallery in power plants, an improved algorithm with 3D-Harris operator about corner detection is proposed. In this algorithm, firstly, taking multiple sets of massive point cloud data of the underground pipe gallery as analysis object, the normal information of the target detection point on the adjacent point cloud microtangent plane is obtained through principal component analysis method, thus the boundary points of the point cloud are extracted. Secondly, the covariance matrix is constructed according to the normal information of the target detection point, then the corner response intensity function is calculated and compared, and some points are selected as calculation objects to judge whether they are true corner. Thirdly, the pseudo angles are filtered out and the true angles are selected by using a pseudoangle detection method based on Gaussian curvature extreme points. At last, the fast point feature histogram method is used to match similar corners between each group, and the nearest point search point cloud registration algorithm is used to realize the splicing of multiple points and cloud in the underground pipe gallery. The results are compared with that of the conventional 3D-Harris angular point detection algorithm. It is proved that the method in paper takes less time to calculate and has a higher corner-point extraction accuracy, which can realize accurate splicing of massive point cloud of underground pipe gallery.

The high-temperature and high-pressure (300 ℃/10 MPa) corrosion electrochemical behavior and oxide film microscopic features of Incoloy 800H alloy aged at 675 ℃ for 0~10 000 h in alkaline environament were investigated systematically. By means of electrochemical test, long-term immersion test, scanning electron microscope/transmission electron microscope observation, Raman spectroscopy/fast Fourier transform analysis and other methods, the electrochemical activity, evolution of oxide film morphology and composition characteristics of the 800H alloy with extension of aging time were systematically studied. The results show that, the value of open circuit potential and self-corrosion potential E_corr of the 800H alloy in high-temperature and high-pressure water can be slightly increased by aging treatment, but the effect of aging time extension on the electrochemical behavior was not significant. A passive to trans-passive process was depicted. The oxide film of the 800H alloy formed in high-temperature and high-pressure water had a multilayer structure: the most outer layer was the dispersed large particle oxides composed of Fe₂O₃ or NiFe₂O₄; the middle layer was relatively compact small size oxides, mostly NiFe₂O₄ or FeCr₂O₄; while the inner layer was dense and continuous oxides, amorphous or nanocrystalline oxide containing Cr and a small amount of Fe. The 800H alloy has good corrosion resistance and surface stability in alkaline high temperature and high pressure water of 300 ℃/10 MPa.

In order to select high activity catalysts for urea hydrolysis, the kinetic and thermodynamic characteristics of urea catalytic hydrolysis reaction were studied by using batch reactor and continuous operation pilot plant, and the effects of different catalysts on hydrolysis reaction temperature, energy consumption and variable load response time were compared. The results show that, the activation energy of the hydrolysis reaction can be reduced by adding catalyst (the activation energy of the liquid diammonium hydrogen phosphate is 65.3 kJ/mol, and that of the solid alumina is 52.9 kJ/mol), and the urea conversion can be improved. The addition of catalyst increases the hydrolysis reaction rate and decreases the hydrolysis reaction temperature. Due to uneven distribution and insufficient contact, the catalytic activity of solid alumina catalyst decreases in the continuous operation reactor. The energy consumption of ammonia production by catalytic hydrolysis is about 1%~3% lower than that of ordinary hydrolysis, and the response time of hydrolyzer changing load is not shortened by adding diammonium phosphate and alumina catalyst.

In order to study the corrosion behaviors of candidate materials for superheater of supercritical boilers in high-temperature flue gas environment, three austenitic heat-resistant steels including S31042, S31035 and C-HRA-5 were exposed to laboratorial simulated coal-fired flue gas for hot corrosion tests. The tests were carried out at 650, 675, 700 and 725 ℃. On the sample surface, there were three conditions including no coating, coating with real coal ash, and coating with corrosive simulated coal ash. The test duration was 500 h. The corrosion kinetic curves of the three materials were obtained through experimental research, and corrosion behaviors of the material were analyzed by XRD, SEM and EDS. Moreover, corrosion resistance of the three materials was compared. The results indicated that, the three materials had excellent resistance to oxidation and corrosion under the conditions of no coating and coating with real coal ash. Under the condition of coating with corrosive simulated coal ash, the material corrosion intensifies and the corrosion products are layered. The temperature effect was different under different coating conditions. S31042 had the best corrosion resistance, and the corrosion resistance of S31035 and C-HRA-5 materials was comparable.

Large-scale grid connection of new energy power generation makes cogeneration units need flexible operation to smooth out the fluctuation brought by new energy access. In order to meet the control requirements of flexible operation of the unit and the safety of the unit operation, a flexible control strategy for cogeneration units based on flexibility evaluation is designed. Firstly, according to the response characteristics of electrical load, thermal load and throttle pressure of the unit, a calculation method of flexibility evaluation indexes which can represent the load adaptability and operation safety of the unit are proposed, and these indexes are used as the basis for selecting the optimal flexibility factors. Then, the influence of flexibility factor on the system performance under a single working condition is simulated. Finally, on the basis of determining the optimal flexibility factors under different working conditions, the adaptive flexibility factors that changing with working conditions are designed and applied to the flexible control. The simulation results show that, the control strategy can not only achieve a better control effect when the unit runs under large-scale conditions change, but also achieve a better control for the unit after the low-pressure cylinder is cut off, which can meet the control requirements of flexible operation of the unit and ensure the safety of the unit operation..

Voltage transformer (TV) interturn short circuit at generator outlet will cause unbalanced voltage in system, resulting in zero sequence stator ground fault protection of generator fundamental. The external characteristics of TV fault are of great significance to stable operation of the unit. In order to understand the external characteristics of TV fault, based on Maxwell and Simplorer software, a field circuit direct coupling finite element model for the electromagnetic conversion process of single-phase voltage transformer is established, which can realize data exchange between field circuits at each calculation step. In view of the large number of turns of TV primary winding, which is difficult to model directly, winding grouping technology is proposed. An experimental platform is designed and built to verify the accuracy of the simulation model. Based on the calculation results of finite element eigenvalues, the electrical and magnetic eigenvalues of TV in different operating states are analyzed, and the analytical model of TV inter turn fault based on winding grouping technology is further given. The simulation results show that, the TV turn-to-turn fault model is accurate and effective in analyzing the primary current, circulating current and other fault characteristic quantities.

As a nondestructive testing method, magnetic particle testing is widely used in power industry. The comprehensive sensitivity of the magnetic particle detection can be tested by A1 standard shims. However, at present, the evaluation of the clarity of magnetic trace on standard shims still depends on subjective judgment of the tester. In order to eliminate the subjective factors in the evaluation, this paper proposes a standard magnetic trace evaluation method based on machine vision. Based on Python programming language and OpenCV function library, the initial obtained magnetic trace is processed by image correction, magnetic trace extraction, quantitative analysis and evaluation using computer program. On this basis, the influence of the thickness of non-magnetic layer on the comprehensive sensitivity of magnetic particle detection is investigated using this method. It is shown that the magnetic trace evaluation method based on machine vision is more objective and accurate than the conventional manual evaluation.

As a clean and efficient power generation technology, solar thermal complementary combined cycle power generation (ISCC) system is concerned widely. By taking the ISCC system containing three-pressure reheat combined cycle and trough solar field as the research object, and based on the conventional trough ISCC system (using solar energy to replace the high pressure evaporator (system 1)), two new trough ISCC system are presented, namely using solar heat collection field to replace the high and medium pressure evaporators simultaneously (system 2), and using solar heat collection field to replace the high, immediate and low pressure evaporators simultaneously (system 3). Moreover, the dynamic performances of the above three ISCC systems are analyzed under the operation condition of typical day. The results show that, with proper operation strategy presented above, the three systems can not only realize safe and stable operation, but also reduce the impact of solar energy varies on the ISCC system output power. Under the operation condition of typical day, the second type of ISCC system (system 2) has better thermal performance.

Blade fractures and cracks occurred on low pressure second last stage moving blade of a steam turbine before and after the blade optimization. In order to find out the cause of this type blade failures and prevent subsequent reoccurrence, the blade failure, operating parameters and historical records were checked, and the materials and fractures of some failed blades were analyzed through physical and chemical inspection. Moreover, the centrifugal stress of the blade and the vibration characteristics of the gear train before and after optimization were numerically analyzed by finite element method. The results show that, the blade fracture is a high peripheral fatigue fracture. Before optimization, the main reason for cracks and fractures at the connection transition between the top of the inner cambered surface and the shroud on the steam outlet side of the blade is that the blade has a large torsional recovery under working conditions, resulting in severe compression of the shroud, and stress concentration and fatigue damage occur at the connection transition between the top of the inner cambered surface and the shroud on the steam outlet side. The unreasonable design of blade root structure is the main factor for high cycle fatigue cracking of blade root, while the vibration of the sixth pitch diameter of the first stage of blade impeller system falling into the "3-coincide point" resonance area is the secondary factor for blade failure. After optimization, the main reason for the fracture is the unreasonable design of the blade root structure, and the vibration of the eleventh pitch diameter of the second stage of the blade impeller system falling into the "3-point" resonance area is the secondary factor causing the blade root failure.

To solve the problem of low recognition accuracy of transformer insulation oil gas fault diagnosis, the slime mold algorithm (SMA) is improved by the reverse learning strategy to form the improved slime mold algorithm (ISMA), thus to improve the global optimization ability and optimize the support vector machine (SVM). An ISMA-SVM optimized fault diagnosis model is established, and the sample set is used for learning and training. The diagnosis and recoginition results are compared with that of the greywolf algorithm (GWO-SVM) and the particle swarm optimization (PSO-SVM), it shows that the accuracy of the ISMA-SVM fault diagnosis and recognition is 93.3%, which is 6.66 and 10.66 percentage points higher than that of the GWO-SVM and PSO-SVM, respectively.

Welding of dissimilar steels is a widely used connection method for super-heater tubes of boilers in power plants. Taking the TP304H/T22 dissimilar steel welded joint with backing plate at the superheater outlet of a thermal power unit as the research object, the formation mechanism and influence of cracks in the welded joint are analyzed through macro measurement, microstructure analysis, EDS energy spectrum detection and tensile test. The results show that, the differences in thermal expansion coefficients of the three substrates and stress concentration are the cause of the cracks of the dissimilar steel weld with backing plate and crack propagation in nickel base weld filler. The weld is the weak link in room temperature tension, while the fusion line and base metal are the fracture parts in high temperature tension.

In order to realize zero liquid discharge, a power plant treated circulating wastewater by the combination process of two stage softening and clarification, media filtration, ultrafiltration, nanofiltration (NF) and reverse osmosis (RO), and treated terminal wastewater by the combination process of chemical softening, tubular microfiltration (MF), NF, seawater desalination reverse osmosis, electrodialysis (ED) and evaporative crystallization. After the above measures were taken for 1 year, insufficient NF output was found in the circulating wastewater treatment system, and serious MF membrane organic fouling and ED silicon scaling was observed in the terminal wastewater treatment system. Thus, the causes of the membrane fouling was analyzed and the desulfurization process water was optimized to reduce the chemical oxygen demand (COD) of desulfurization wastewater from the source. Moreover, the MF operation mode was optimized, so as to slow down the MF organic pollution phenomenon. In addition, the RO concentrated water of circulating water treatment mode was adjusted, and the total silicon mass concentration was reduced to less than 1 mg/L before being fed into the ED equipment, to solve the problem of the ED silicon scaling.