The failure of boiler tubes in thermal power units will cause non shutdown of units and greater economic losses. Deposits in boiler tubes are an important reason for their failure, and reducing deposits in boiler tubes is of great significance to the safe and stable operation of units. It is found that the formation of deposits is related to many factors, such as overheating of furnace tubes, high heat load, poor water vapor quality, water vapor phase transition, working medium disturbance and pipe surface defects. Combined with the flexibility of units, deep peak shaving operation, environmental protection reform and other conditions, the formation mechanism and influencing factors of various types of deposits are analyzed with actual accident case pictures. The effects of overheating, salt concentration and corrosion under scale caused by deposits in furnace tubes are further discussed. The countermeasures for feedwater quality, boiler shutdown protection, unit startup steam purification, unit peak shaving, boiler tube replacement, boiler transformation and maintenance are proposed, which can effectively reduce the generation of boiler heating surface deposits and reduce the risk of boiler tube failure.

The power industry is the core of the energy system as well as a major carbon emitter. The zero-carbon development of it is the key to the process of carbon neutralization in China. From the perspective of carbon emission, energy resource endowment, industry status, existing problems and development trend, the general situation, low-carbon development path and effect of the electric power industry in the United States, Germany, France and Britain in the European Union was analyzed. Several enlightenments combined with the current situation of the electric power industry in China were summarized, hoping to provide reference for the low carbon development of Chinese electric power industry.

The analysis of heat and mass transfer process has important guiding significance for the performance improvement of heat and mass transfer equipment. Through the analysis of the thermal resistance in the boundary layer, the author explores the development of the convective thermal resistance and thermal conduction thermal resistance in the laminar flow of the pipeline in the boundary layer, and establishes a mechanism model (R-P model) that conforms to the macroscopic characterization. The thermal resistance distribution law under the condition of Re and Pr, explored the internal mechanism of laminar flow enhanced heat transfer in the tube, and guided the optimal design of the flow-around structure. The results show that the heat conduction is absolutely dominant in the inlet stage, and the proportion of convection gradually increases after the full development. The mechanism of Re and Pr affecting heat transfer is different. When Re increases, the heat transfer must be strengthened. When Pr increases, it only increases the proportion of convection, and in the range of (Pr<1.8), thermal resistance always plays a major role. At the same time, it was found that adding a turbulent flow structure to the laminar flow in the pipeline would reduce the heat transfer effect.

Ammonia is a kind of zero-carbon fuel with mature technology and low storage and transportation cost. Partial replacement of coal with ammonia can become an effective way to reduce carbon at the front end of coal-fired units under the dual carbon target. Ammonia fuel is studied as an alternative fuel. The fuel characteristics of ammonia and its blended fuel with typical bituminous coal are studied by using one-dimensional flame furnace and ignition furnace. The ignition performance changes of ammonia/coal blended fuel, the enhanced combustion and pollutant control technology of different proportions of ammonia blended fuel are studied and analyzed in detail. It is found that the pre-blended combustion of ammonia/coal is not conducive to NO_x control. Through fuel grading, combustion excess air coefficient or oxygen control, and air staged combustion, lower NO_x generation concentration and better combustion effect can be achieved during ammonia blending. The operation control suggestions of 25%ammonia mixed with typical bituminous coal are obtained.

The carbon content of fly ash in boilers is one of the important indicators of combustion efficiency. This study employs machine learning models to accurately predict the carbon content of fly ash. Firstly, random forest is employed to adjust the frequency of fly ash carbon content data to once per minute, aligning it with the input features to address the issue of imbalanced data collection frequency. Then, a recursive feature elimination method based on random forest is used to extract nine important features out of the original 30 features, reducing feature correlation and improving model accuracy. Subsequently, six machine learning models (linear regression, decision tree, K-nearest neighbors (KNN), random forest, Catboost and XGBoost) are compared for prediction. The results indicate that decision tree, KNN, random forest and XGBoost models perform well, MSE of which on the test are 0.010, 0.009, 0.006 and 0.006, respectively, while linear regression exhibits the poorest performance. The prediction models remain robust under low, medium, and high boiler loads.

In order to use the market mechanism to reduce carbon dioxide emission and promote green low-carbon transition, countries around the world have successively built carbon emission trading markets. Carbon dioxide emission monitoring technology is the main technical method to achieve accurate carbon emission measurement. It is an important technical support to assist the carbon emission accounting system. This paper focuses on the analysis of the current situation of carbon dioxide emission monitoring and accounting in the power generation industry, and introduces the carbon dioxide emission monitoring methods in the power generation industry in detail, including emission factor based method, online monitoring method, carbon balance method, soft sensing method, and satellite monitoring method. In view of these monitoring methods, this paper systematically reviews the researches of carbon dioxide emission monitoring methods in the world, expounds the advantages and disadvantages of the monitoring methods, compares the methods from accuracy, timeliness, reliability and monitoring cost, and provides reliable technical solutions for carbon dioxide emission monitoring in the power generation industry. Finally, we make an outlook on future research directions and practical applications.

In order to solve the problems of high pollutant emission mass concentration, low energy utilization rate and high initial investment cost of conventional waste disposal power station, combined with the green transformation development needs of coal-fired power station. This paper proposes the technical ideas of coal-fired boiler station coupled with waste. A 30 t/d coal-fired boiler station coupled waste was built to analyze and study the impact of system operation on the efficiency of coal-fired power station, pollutant emissions and energy efficiency of waste disposal. And this paper uses three coupling methods of hot air, flue gas and steam water to achieve efficient and clean disposal waste on large coal-fired power station. The results show the three coupling methods are completely feasible to achieve efficient and clean disposal waste. The coupling of hot air can improve the effect of disposal waste and reduce the carbon content of fly ash and slag; the coupling of flue gas can ensure conventional pollutants such as SO₂, NO_x and dust reach the emission level of coal-fired power station without increasing the emission of dioxins. The coupling of steam water can improve the energy efficiency of disposal waste. This technology provides new technical ideas for the disposal of organic solid waste and has a broad application prospect.

The intelligent retrofit of coal-fired power generation units is an inevitable choice for improving energy efficiency and promoting green industrial transformation. Based on practical requirements and engineering perspectives, this article designs the overall framework and key technologies for the intelligent retrofitting of wet flue gas desulfurization systems. First, the structural components of the intelligent control system (ICS) network framework are discussed. Next, based on the ICS framework, an optimized control strategy combining information-physical fusion models and advanced control algorithms is designed, as well as an optimized control strategy for the absorption tower pH value based on the direct energy balance (DEB) approach. Simultaneously, the information-physical fusion optimization results guide the analysis of the intelligent evaluation system. Using data twin technology and mechanism models, intelligent early warning and fault diagnosis for the system are achieved. By analyzing typical faults, an expert system is established, combined with data-driven techniques for real-time fault tracking. Finally, the article points out that a visualization-based human-machine interaction system is used for real-time display of desulfurization system indicators, constructing an integrated desulfurization system that combines ICS, digital twins, machine learning and visualization. This provides a basis for realizing a self-optimizing, self-learning, self-recovering, self-organizing and self-adaptive intelligent desulfurization system.

Rapid and accurate measurement of the calorific value of incoming coal is the essential to provide guidance for the economic and safe operation of power plants. However, coal has complex components, and the calorific value is correlated with elemental composition and molecular structure, it is difficult to measure coal calorific value quickly and accurately by a single analytical technique. Based on laser-induced breakdown spectroscopy (LIBS) and near-infrared reflectance spectroscopy (NIRS), a method is proposed to detect the calorific value of incoming coal by combining two techniques. The LIBS and NIRS spectral signals of the coal on the conveyor belt are collected simultaneously. Fusion of two spectral information after data pre-processing, coupled with partial least squares (PLS) modeling method to quantify coal calorific value. This method is used in a coal sample measurement system built by lab, it is reached that the coefficient of determination of the calibration set was 0.98, and the root mean square error of the prediction set was 0.37 MJ/kg, with an average absolute error of 0.26 MJ/kg and an average relative error of 1.09%. The results show that the proposed method of simultaneous acquisition of LIBS and NIRS signals can measure coal calorific value rapidly and accurately.

Condensate downcomer vibration is a common phenomenon in the direct air cooling system, which endangers the safe operation of the air cooling system when the vibration is serious. The pipe vibration model is established based on the fluid solid coupling method. The two-phase flow characteristics of the condensate pipe are analyzed using the theory of flow induced vibration and fluid cavitation. The model analytical calculation and numerical simulation are carried out for the condensate pipe of a 660 MW ultra supercritical unit. The results show that saturated or nearly saturated condensate flows from the air cooling platform along the condensate downcomer to the hot well of the steam exhaust device by gravity flow. When the potential energy of water is released, two-phase flow excitation and cavitation phenomena occur. Based on this analysis, the causes of condensate vibration and cavitation noise are found, By using multi-stage Venturi tubes and porous orifice plates in the condensation water pipeline of the power plant to eliminate the condensate potential energy, avoid excessive pipeline vibration and noise, and eliminate the hidden danger of pipeline vibration.