As a fundamental component of the organic Rankine cycle (ORC), the scroll expander's operating characteristics critically influence the ORC's overall performance. Initially, we establish a three-dimensional transient simulation model of the scroll expander. This allows us to systematically analyze the effects of various operating conditions on aspects such as suction pressure, exhaust pressure, rotational speed, and the output power and isentropic efficiency of the scroll expander, using numerical simulation. Following this, we study the effect of different operating conditions on the transient performance and mechanical properties of the scroll expander, and achieve a more comprehensive understanding of the mechanisms involved. Ultimately, we verify the accuracy of our numerical model using a laboratory-built test bench of the ORC low-temperature waste heat oil-free power generation system. The close correlation between the experimental results and numerical simulation outcomes authenticates the reliability and applicability of our numerical simulation method. In conclusion, this research's findings offer significant referential value for the design and optimization of the scroll expander.

Although the reserves of high-alkali coal represented by Zhundong coal is huge, the problem of coking on heating surface of the boiler is prominent during co-firing high-alkali coals in thermal power units, which not only reduces the boiler thermal efficiency, but also seriously threatens the safe, stable and economic operation of the unit. In order to solve this problem and promote the utilization of high-alkali coal, this paper reviews the researches on coking of the heating surface of high-alkali coal boilers and the prevention. Up to now, extensive researches have been carried out at home and abroad on the characteristics of coking on the heating surface of coal-fired boilers, coking mechanism, influencing factors, prevention and control measures, and so on, and fruitful research results have been achieved. On the basis of controlling the quality of coal, improving boiler structure, and optimizing boiler operation, the preparation of coating on the heating surface of boilers has also become an important technical path for preventing and controlling coking. In the future, the coating should possess excellent comprehensive properties such as high temperature resistance, corrosion resistance, wear resistance, thermal conductivity, thermal fatigue and so on, while having outstanding coking resistance. Meanwhile, the coating also should have desirable preparation economy and preparation efficiency, especially the on-site applicability.

Further research on slag-tap boiler can promote the application of fully burning high-alkali coal technology. In this study, a supercritical 350 MW once-through double-U flame slag-tap boiler is taken as the research object and the combustion chamber, slag collection tube bundle and cooling chamber are taken as the calculation units, the thermal calculation is performed from the perspective of heat balance. The flow field, temperature field and component field in the boiler under design condition and at variable loads are studied. The deviations of several flue gas temperature results obtained by thermal calculation and numerical simulation are within 40 K. At the outlet of the combustion chamber, the deviation is only 1.2 K. The temperature deviation of flue gas at the outlet of cooling chamber is 15.6 K. After verification and comparison, it is concluded that the thermal calculation method adopted can be applied to the thermal calculation on double-U flame slag-tap boiler that fully burning high-alkali coal. The flow field is well organized. The recirculation zones formed by swirling flow can increase the movement path of pulverized coal particles in the combustion chamber and promote the burning. When the flue gas flows through the slag collection tube bundle, the temperature greatly reduces. The flow field is also disturbed, which can effectively capture the ash. At variable loads, the velocity field in the boiler decreases proportionally according to the reduction ratio of the amount of coal. However, the size of the recirculation zones is basically unchanged. The temperature level in the boiler reduces, when the amount of coal reduces from 100% to 75%, the flue gas temperature at the outlet of the combustion chamber reduces by about 75 K, and the flue gas temperature at the outlet of the cooling chamber reduces by about 200 K. This study can provide reference for fully burning high-alkali coal in double-U flame slag-tap boiler.

In order to understand the key parameters and operating experience on fully burning and high proportion blend burning high-alkali coal in boiler with slag-tap furnace, long-term engineering tests were conducted based on a 300 MW boiler with slag-tap furnace in a power plant. An analysis was conducted on the possible combustion organization, nitrogen oxide control, slag flow, and ash deposition issues. Modifications were made to the combustion system, thermal modification system, and slag flow system. So long-term operational data and key parameter records were conducted, after fully burning and high proportion blending burning of 300 000 tons of high-alkali coal, all operating parameters of the boiler were normal. Based on recent operations and comprehensive tests, the optimized boiler with slag-tap furnace in a specific power plant demonstrates strong adaptability to high-alkali coal. Within the control range of coal ash components with w(Al₂O₃)<25%, w(Fe₂O₃)<15%, 12%<w(CaO)<30%, silica-alumina ratio>1.7, acid/alkali ratio>0.5, the normal operation of the boiler can be ensured without obvious ash deposition. Burning high-alkali coal can effectively reduce the inlet flue gas temperature of the first-level heating surface to below the design value, effectively avoiding the occurrence of slagging on the first-level heating surface of the boiler, and the generation of nitrogen oxides is also reduced by more than 30% compared with using the original design coal.

To enhance the whole process safety of fan operations and ensure accurate fault diagnosis and long-term production income of thermal power plants, predicting these risk issues is crucial to enhance the safety of the unit. In this paper, we proposed a fan fault diagnosis model of big data platform that integrates multilayer perceptron and polynomial fitting. The fan early warning model was established by multilayer perceptron and polynomial fitting modeling technology, and integrated into the big data platform to find abnormalities which were difficult to find manually during the operation of the fan. By combining data mining with mechanism analysis and feature value knowledge base, the parameters boundary information of fan stall could be excavated, the stall boundary conditions of the fan were accurately configured under various working conditions, and a stall boundary condition diagram was created. By combining those informations with normal operating conditions, the early stall zone can be obtained. Finally, a fault diagnosis model that covers the entire working condition of the fan can be established. Utilizing the comprehensive big data platform that covers, circulates, and maintains fan operation data, a system of intelligent fan patrol model was constructed. The intelligent patrol disk model which replaces the operator was then used to monitor and diagnose the fan running state regularly, which can achieve accurate and safe diagnosis of fan faults, minimize the fault incidence and maximize the personnel reuse rate.

FMEA is an effective reliability analysis method for identifying potential failure modes in a system and evaluating their criticality. Conventional FMEA has many shortcomings such as not considering the weights of different risk factors, RPN being very sensitive to changes in risk factors, difficulty in handling expert subjective scoring information, and not considering the propagation and impact relationships between failure modes. Aiming at these shortcomings, an improved FMEA method was proposed by introducing house of reliability, rough set theory and VIKOR method to improve the accuracy and objectivity of risk priority analysis of failure modes. Compared with the conventional FMEA, the improved FMEA can not only effectively deal with the various subjectivities and uncertainties in the risk assessment process but also rank the risk of the identified failure modes with taking into account the effects of failure propagation, which is able to rank the risk priority of failure modes in the case of attribute conflict and various uncertainties. Based on the proposed FMEA, a real-word application of risk priority ranking of the failure modes in wind turbine was carried out and the risk priority order of each failure mode and each subsystem were obtained. According to the ranking results, the weak links and key subsystems of the reliability of wind turbine were identified, and the hazard weight of each failure mode and subsystem was given, which can provide data support for the reliability optimization design of wind turbine.

As a kind of slag-tap boiler, cyclone-fired boilers exhibit significantly different aerodynamics comparing with pulverized coal (PC) boilers. However, by far there are still lack of CFD models that are able to provide effective guidance to the design and operation of cyclone-fired boilers. A CFD model of cyclone-fired boilers was developed in which the capture of coal particles by the molten slag layer was considered through a slag layer coal particle capture model. This model was then employed to investigate the aerodynamics and flue gas recirculation (FGR) optimization design of a 550 MW cyclone-fired boiler. The results demonstrate the highly nonuniform characteristics of furnace aerodynamics of cyclone-fired boilers due to the strong swirling flows created by the cyclones leads to the formation of localized high temperature zones and severe boiler fouling problems at the entrance of boiler convection pass. Thus, it is critical to adapt the FGR design with the nonuniform furnace flow and temperature distributions. The simulation results show that, with the optimized FGR design, the high temperature zones and the resulting severe fouling problems were effectively mitigated.

With the continuous increase of installed capacity of new energy generation in power grid, thermal power units have to undertake more peak shaving. However, the flexibility and peak shaving capacity of current thermal power units are generally insufficient. A subcritical 300 MW coal-fired unit is retrofitted for molten salt energy storage. Six heat storage strategies and two heat release strategies are proposed and investigated. The influence of heat storage and release process on the peak shaving capacity and thermal performance of the unit under three working conditions is analyzed, the technical and economic analysis is performed in terms of the net present value. The results show the feasibility of extracting reheated steam for heat storage is higher, with a peak shaving depth of 58.9%. However, the coal consumption would increase at the same time. During the releasing heat stage, the maximum increment of power generation up to 11.3% of the rated power generation is achieved by heating the water supply to generate steam, while the higher temperature of the molten salt is required. Using high-temperature molten salt instead of low-pressure heater to preheat water supply is proved to have more advantages, while the power generation increment is relatively small. During the whole process of heat storage and release, the maximum circulating electricity efficiency can reach 0.987. The economic analysis of heat storage transformation is conducted. The dynamic investment payback period is 11.65 years, and the net present value is 49.118 million yuan. Therefore, the renovation scheme is feasible.

In order to explore the effects of mixed coal combustion on reducing the carbon content of fly ash in a subcritical 600 MW natural circulation balanced draft boiler, three types of coal with significant differences in characteristics were used, and numerical simulations were combined with experiments to study the mechanism of mixed coal combustion and its relationship with fuel characteristics, burnout rate, and carbon content in fly ash in the stratified combustion process of the balance boiler. Based on the results, a set of coal blending principles are proposed to improve the combustion characteristics of coal powder in power station boilers. Firstly, three extreme operating conditions were set up, and high-quality coal was respectively focused on the upper, middle, and lower layers of the burner for combustion. And then, through computational fluid dynamics (CFD) simulations, it was found that when the coal powder airflow of the balance combustion boiler flowed upward, and the high-quality coal was distributed in the upper layer of the combustion chamber while the poor-quality coal was distributed in the lower layer, the residence time of poor-quality coal in the furnace increased significantly, allowing it to fully combust in the high-temperature area of the upper layer, resulting in a low carbon content in fly ash. Furthermore, based on the analysis of the heat value, volatile matter and ash content of coal powder in different combustion layers under various working conditions, it was found that the difference in heat value and ash content is the main factor influencing combustion characteristics. Based on the actual operating conditions of the coal-fired power plant, a more realistic set of coal blending scenarios was established, and numerical simulations and on-site experiments were conducted, which showed that the overall combustion characteristics of coal powder under each working condition followed the aforementioned rules, and the carbon content in the fly ash reduced compared with the original operating conditions. Finally, the coal blending principles were established, which take into full consideration of the actual operating conditions of the power plant, recommend high-quality coal with low ash content to be used in the upper and middle layers of the combustion chamber while poor-quality coal with high ash content should be used in the middle and lower layers of combustion burner.

As a large number of new energy is connected to the grid, the participation of supercritical thermal power units in peak regulation tends to cause the superheat of intermediate points to fluctuate greatly, resulting in superheated steam over temperature and other problems. In order to better control the intermediate point superheat to achieve stability, a prediction method of intermediate point superheat based on double-depth input convex neural network multi-model (muti-DDICNN model) was proposed. Sub-models with different prediction step sizes were trained respectively, and the intermediate point superheat state prediction network (SPNN) and error prediction network (EPNN) were constructed. Based on the convex property of prediction network, a multi-model predictive controller (DDICNN-MPC) based on convex neural network with double-depth input is designed. The control problem is transformed into a convex optimization problem, the Jacobian matrix of control matrix to objective function is obtained, and the optimal solution of control matrix is calculated by gradient descent method. The simulation results show that, the DDICNN-MPC can track the intermediate point superheat setting quickly and stably, and the steady-state error is small, so it has good adjustment ability.