In order to realize efficient and accurate detection of the pitch bearing tooth surface of wind turbines in service under the adhesion of high viscosity lubricating grease, profiling array eddy current technology is used to study the effects of different coil arrangement methods and lifting distances on the detection results of bearing tooth surface defects. It can be concluded that, the edge effect range of Z-shaped and composite coil layout is different, and the composite profiling probe is significantly shorter than the Z-shaped probe. By detecting the artificial groove defects of 10.00 mm×0.50 mm×1.00 mm (slot length × slot width × slot depth), it indicates that the lifting distance limits for inner and outer toothed bearings are 1.04 mm and 1.43 mm, respectively. Experimental verification is conducted on the in-service fan bearings under the condition of high viscosity lubricating grease on the surface, and the results of defect size and position detection are accurate, with an error of less than 5%. This provides technical support and new ideas for supervision and inspection of the pitch bearing gear tooth surface in service.

To unveil the ultra-low load operating characteristics and performance optimization method of large-scale units burning high moisture lignite, the influences of burners operating scheme under 33%BMCR condition on the coal combustion, heat transfer and NO_x transformation characteristics of a 660 MW unit utility boiler were investigated, based on an established and validated simulation model of coal-fired boiler. The results show that, well-organized flow and combustion field can still be formed inside the furnace under ultra-low load condition, but the overall boiler performance deteriorates evidently, such as obvious decreases in combustion temperature and heat transfer intensity, and increase in NO_x emission at outlet of the furnace. When 4 layers of burners are in-service, continuous lower-middle groups or middle-upper groups of burners should be put into operation, to prevent the significant deteriorations of combustion and heat transfer processes and the significant increase in NO_x emissions. The number of in-service burners layers significantly affects the overall boiler performance. When there are only two layers of burners in-service, the intense coal combustion area is too concentrated, which is not conducive to maintaining a high combustion temperature and heat transfer intensity, and NO_x emissions at the furnace outlet increase at the same time. These findings reveal the influences of burner operating scheme under ultra-low load condition on the overall performance of a 660 MW lignite boiler, which can provide guidance for deep peak shaving operation adjustment and optimization of coal-fired units in the context of large-scale renewable energy power grid connection in the future.

The HT700 superalloy was joined by rotational friction welding (RFW) method, and the welded specimens were subjected to post weld heat treatment (PWTH). The microstructural evolution and mechanical properties of the joints were systematically investigated by optical microscopy, scanning electron microscopy, transmission electron microscope, micro-hardness, and tensile tests at both room temperature and 750 ℃. The results show that, the as-welded joint shows three typical zones across the weldline: weld center zone (WCZ), thermomechanically affected zone (TMAZ), and heat affected zone (HAZ), in which the microstructure gradually changes from equiaxed fine grains (WCZ) and deformed coarse grains (TMAZ) to equiaxed grains (HAZ) that are similar to the base material. The dynamic recrystallization and dissolution of strengthening phases have occurred in the WCZ during RFW, in which γ′ strengthening phase dissolves to a larger extent than M23C6 or MC carbides. The microstructure of the as-welded joint including the grain size, shape, and the distribution of precipitates gradually changes from the weldline to the parent alloy. Consequently, the as-welded joints exhibit relatively poor mechanical properties due to the dissolution of γ′ which becomes even worse at 750 ℃ because of the grain-boundary sliding. After PWHT, the as-welded microstructure can be homogenized by grain growth and the re-precipitation of strengthening phases, which is responsible for the remarkable improvement in tensile strength at both room and high temperature after PWHT. And the high-temperature ductility of PWTH joints has been improved to a certain extent. This study gives new insights into the high-quality welding of the HT700 superalloy.

Raw water pretreatment can be divided into three stages: coagulation, sedimentation and filtration. The flocculation process directly affects the structure of alum and the turbidity of effluent. At present, the method of measuring the turbidity of the effluent is usually used to control the dosage of coagulant, but due to the time lag, it can not quickly reflect the coagulation effect and adjust the dosage of the feedback. With the rapid development of computer technology, the application of alum image processing technology can realize rapid, accurate and real-time detection of flocs state, so as to control the dosage more accurately and improve the coagulation effect. From the perspective of computer vision technology, this paper summarizes the technical characteristics of alum image acquisition and processing in flocs, introduces the method of real-time tracking and calculating the characteristic parameters of alum structure, such as equivalent particle size, fractal dimension, etc., and some test results are also provided. Through these parameters the best coagulation effect can be judged, which provides the basis for coagulation control and dosing.

At present, domestic research on gas control valves or other equipment in gas turbines is still lacking, while most of these researches’ models remain in a single hydraulic valve or a hydraulic cylinder. So this paper uses Simulink/Simscape software to model the entire gas turbine’s gas control valve including the PI controller to the gas pipeline, and conduct simulation analysis for faults such as fixed orifice blockage, wear of the spool valve core and hydraulic oil contamination to discuss their forms and causes. The result shows that, the blockage of the one-sided fixed orifice of the nozzle damper valve, the wear of the slide valve core and the impurities in the hydraulic oil will all cause the valve to respond slowly, or even become clogged and stuck to varying degrees. Finally, for the monitoring of valve data in current power plants some suggestions are thrown out: according to the actual operating conditions, monitoring of the parameters such as the servo valve spool displacement signal and hydraulic cylinder piston displacement can be introduced by using electronic feedback servo valve, to better judge the health status of the valve.

In the context of current energy structure transformation, conventional thermal power would gradually transform into grid source support and system regulation. Coupling with distributed photovoltaic power is an effective attempt for thermal power enterprises to achieve cost reduction and efficiency improvement. However, due to the lack of relevant guidance for the connection of non centralized power sources for the factory use, there is a lack of evaluation strategies and empirical references for system security and stability. For this purpose, taking the thermal photovoltaic complementary energy supply system of a thermal power plant in northwest China as an example, its operating characteristics are analyzed and a technical framework for stability evaluation is provided. In examples of different power units, grid connection levels, and minimum photovoltaic unit layout, application evaluation issues such as static power flow, transient stability, and power quality are discussed. It is calculated that the power consumption reduction efficiency of thermal power units in this case achieves an improvement of 18%~42%. This conclusion has typical reference significance for the application of the power generation technology model of “distributed photovoltaic access to plant use systems” in thermal power plants.

With the increase of various types of cyber-attacks, the security of industrial control systems in energy and power infrastructures has gradually become a focus of attention. Combined with the characteristics of power system, the CNN-LSTM-Attention network intrusion detection algorithm model integrating convolutional neural network (CNN), long and short-term memory (LSTM) neural network and Attention mechanism is proposed. By constructing and collecting the operating state data sets of the pulverizing system of a 600 MW coal-fired unit under three typical operating conditions under cyber-attacks in a laboratory simulation environment, the proposed detection algorithm model is trained and evaluated. The results show that, the proposed intrusion detection algorithm model has the best performance compared with the CNN and LSTM models. The model has the best rating indexes such as accuracy, precision, recall, etc., and the comprehensive evaluation is better than other intrusion detection methods. The intrusion detection algorithm model is highly innovative and practical.

In view of the increasingly serious problem of power grid peak regulation caused by the instability of new energy, combined with the relatively mature photo-coal complementary power generation technology and the multi-heat source combined heating peak shaving system, the light-coal mixed heating power generation system was designed to make the cogeneration unit have a certain peak regulation capacity. Based on the actual operating conditions of the heating unit and the premise of ensuring the heating load, the coupling mode of the solar-assisted dual-engine cogeneration unit was analyzed, and the peak regulation performance of the two-engine was compared before and after coupling. The results show that, a dynamic throttle valve is installed on the pipeline between the condenser outlet and the heat exchanger of the solar collector system, and the operation mode of the auxiliary heating unit of the solar collector system can be changed, which can realize flexible operation of the integrated system of power generation, heating and peak regulation. Among them, the solar thermal collection system is only used for supplementary heating, the peak regulation capacity ratio is 0.76, and the ratio of solar auxiliary double-heating supply before and after peak regulation capacity is 0.55. The No.1 unit which is assisted by solar energy to bear the maximum heating load has the best performance in peak regulation capacity and peak regulation compensation.

Accurately predicting solar irradiation (SI) is crucial for power scheduling and photovoltaic site selection. With the development of high-performance computing and large-capacity storage devices, data-driven deep learning models have gained widespread attentions in the SI prediction domain. However, the lack of physical interpretability due to the “black-box” nature of deep learning models restricts their credibility in specific scenarios. To enhance the interpretability of the model on the premise of maintaining prediction accuracy and keeping the model structure unchanged, and without increasing computational complexity, a model based on long short-term memory (LSTM) neural network is constructed, demonstrating an 8.07% performance improvement over the conventional neural networks and showing superior outlier handling capabilities. By employing layer-wise relevance propagation (LRP) algorithm, factors influencing the model output are scored from both temporal and spatial dimensions, enhancing the model’s interpretability. The research results indicate that the model possesses good interpretability under the premise of ensuring performance, with historical solar irradiation, time-related features (such as hour, day, week, month), solar altitude information (such as sunrise and sunset times), cloud cover, radiation time, temperature, and dew point temperature being the main factors influencing SI prediction.

The increasing volume of sewage sludge production in China has created an urgent need for its harmless and resourceful treatment. This paper aims to tackle this issue by adopting a novel strategy that integrates coal-fired power plants with a sewage sludge drying system, in this method, the sludge will be co-fired after being dried. By taking a typical supercritical 660 MW unit as the research object, the influences of moisture content (10%, 20%, 35%, 50%, and 65%) and blending ratio (2%, 4%, 6%, 8%, and 10%) of the dried sludge on parameters such as flue gas temperature, boiler efficiency, net power generation efficiency, equivalent net efficiency of sewage sludge power generation and equivalent net efficiency of dried sludge power generation are investigated through thermodynamic calculation of the boiler and comprehensive thermodynamic and economic analysis of the entire system under THA condition. The results indicate that, when the moisture content of the dried sludge exceeds 50%, it leads to parameter deterioration, and this trend intensifies with an increase in the blending ratio. Considering all factors, it is recommended to maintain the moisture content of the dried sludge at 50% or below, and if it exceeds this value, the blending ratio should be limited to less than 4%. Blending sludge leads to a reduction in the exergy efficiency of the system, which is mainly due to the increasing exergy losses in the boiler and drying equipment. Moreover, the study reveals that the optimal economic performance is achieved when blending the sludge with moisture content of 20% and blending ratio of 10%, in this case the dynamic payback period is only 4.02 years.