In the context of “carbon peak” and “carbon neutrality”, using renewable electricity to electrolyze water to produce hydrogen and synthesize ammonia can not only consume renewable energy and solve the problem of hydrogen storage and transportation, but also promote the green transformation of the conventional ammonia synthesis process. To investigate the effect of different hydrogen production schemes on technical and economic performance of the synthetic ammonia system, the system thermal and economic performance of three hydrogen production schemes, including proton exchange membrane electrolyzer hydrogen production, proton exchange membrane electrolyzer and alkaline water electrolyzer hydrogen production in a 1:1 ratio, and alkaline water electrolyzer hydrogen production, are compared and analyzed. The hot and cold integration of the synthetic ammonia system with coordinated hydrogen production by proton exchange membrane electrolyzer and alkaline water electrolyzer is analyzed by combining pinch analysis with mathematical programming. The results show that, the system exergy efficiencies of the above three hydrogen production schemes are 60.3%, 56.1% and 52.5%, respectively, and the carbon emissions of ammonia also increase due to the increase in net power consumption of the system. Benefiting from alkaline water electrolyzer’s mature hydrogen production process, the alkaline water electrolyzer hydrogen production scheme has the shortest investment payback period of 6.4 years, while the proton exchange membrane electrolyzer hydrogen production scheme has the longest investment payback period of 12.8 years. The thermal integration analysis of the synthetic ammonia system for the coordinated hydrogen production of proton exchange membrane electrolyzer and alkaline water electrolyzer shows that the low-temperature waste heat below 100 ℃ in the system is released to the environment via cold utilities. In addition, increasing the operating temperature of the electrolyzer is beneficial to improving thermal performance of the system, while lowering electricity price and increasing the annual operating hours of the system will help to improve the economic performance of the system.

The combustion characteristics of coal-fired power plant boilers co-firing ammonia and its impact on the boilers are reviewed, aiming to provide theoretical and practical basis for large-scale application of ammonia as an alternative fuel to coal. By systematically reviewing existing literatures, the study examines the fundamental characteristics of ammonia combustion, flame propagation, flame morphology, and their effects on heat transfer, heat surface safety, boiler efficiency, and exergy efficiency of coal-fired boilers. The study also explores combustion enhancement methods such as oxygen-enriched combustion, preheated combustion, and hydrogen-assisted combustion. The results indicate that, co-firing ammonia can mitigate issues like ash deposition, slagging, wear, and high-temperature corrosion on heating surfaces, but it increases the acid dew point of flue gas, potentially exacerbating low-temperature corrosion. Co-firing ammonia increases the irreversibility of the combustion process, leading to higher furnace losses, although oxygen-enriched combustion can mitigate these losses. While there is substantial research on ammonia co-firing with small molecule gaseous fuels, there is limited study on its co-firing with large molecule solid hydrocarbons like coal. The effect of ammonia blending combustion on boiler heat transfer, heating surface safety, and boiler efficiency is significant. The decrease in flame temperature, reduction in flue gas soots, and changes in flue gas composition can affect heat transfer efficiency and heating surface conditions. Attention should be paid to low-temperature corrosion and unburned ammonia emissions. Ammonia blending combustion is an effective low-carbon combustion technology, but its application in large utility boilers still faces many challenges. It requires further in-depth research on combustion mechanisms and practical application effects to optimize combustion equipment and improve system efficiency.

Focusing on the photo-thermochemical water splitting hydrogen production technology, where photoreaction and thermal reaction are carried out sequentially, the CeO₂ synthesized by sol-gel method and its metal-doped catalysts were taken as the research objects to carry out experimental tests, through which the effects of photoreaction in generating oxygen vacancies and thermal reaction in hydrogen production were investigated. During the photoreaction, CeO₂ catalysts doped with three elements (Fe, Cu, Zn) at three different ratios (5%, 10%, 15%) were used. The metal-doped catalysts were characterized by several methods, such as X-ray diffraction (XRD), transmission electron microscopy (TEM), electron paramagnetic resonance (EPR), photoluminescence (PL), ultraviolet visible diffuse reflectance spectroscopy (UV-Vis DRS), inductively coupled plasma (ICP), and BET specific surface area testing method. The results indicate that, the 10% Cu-doped CeO₂ catalyst exhibits the best photothermal hydrogen production performance. This is attributed to the smallest size of Cu nanoparticles, which results in the smallest bandgap width for the Cu-doped CeO₂ catalyst. Consequently, it can absorb higher energy photons, enhancing the light absorption capacity, and improving the separation and recombination rates of photogenerated charge carriers. This facilitates the formation of photogenerated oxygen vacancies, thereby enhances the hydrogen production capability during the thermal reaction process.

Large-scale hydrogen production technology from renewable energy such as solar power and wind power has become an important pathway for the consumption of renewable energy and the achievement of “dual carbon” goals. The policies and strategic layout of hydrogen energy at home and abroad are introduced, and the advantages and technical bottlenecks of water electrolysis technologies are analyzed. Moreover, the classification, coordination control optimization and energy management of large-scale renewable energy hydrogen production systems are sorted out. In view of the current development status of hydrogen energy in China, a brief analysis of the current installed capacity and the cost is performed, providing a reference for the construction of green hydrogen production system and the clean substitution of terminal energy in China.

A novel type of integrated chemical chain hydrogen production CO₂ zero emission solid oxide fuel cell/gas turbine/organic Rankine cycle hybrid power system is proposed, which achieves efficient power generation while efficiently separating and capturing CO₂. The system uses methane as fuel and generates hydrogen gas through chemical chain reactions to enter the fuel cell, avoiding carbon accumulation inside the cell. The anode outlet circuit of the cell is connected to the chemical chain, and the gas from the fuel reactor outlet and the cathode outlet of the cell enters the gas turbine to do work. The exhaust waste heat is recovered and utilized by the organic Rankine cycle system, further improving the system efficiency. A complete system model was established and thermodynamic performance analysis was conducted on the system, obtaining the variation laws of system performance with fuel flow rate, fuel utilization rate, battery working temperature, and system working pressure. The results showed that the comprehensive energy utilization efficiency of the system could reach over 74.10%, the electrical efficiency could reach over 62.42%, and the exergy efficiency could reach 57.73%. Sensitivity analysis showed that the system performance reached its optimum when the system working pressure reached 7×10⁵ Pa.

Photovoltaic power generation makes full use of the advantages of solar energy, which is green, clean, widely distributed, and abundantly available. However, the efficiency of photovoltaic (PV) modules often decreases as the operating temperature increases, severely affecting system performance. To address this issue, this paper experimentally investigates the cooling effect of phase change materials (PCM) with Y-shaped fins on PV cells. The study focuses on analyzing the effect of structural parameters such as the branching angle, position length, and length ratio of the Y-shaped fins on the system’s thermoelectric performance. The results show that, comparing with the system without fins, the system with Y-shaped fins has an average increase of 0.37% in photoelectric conversion efficiency, and the average melting rate of paraffin increased by 21.52%. The position length has the greatest impact on the melting rate. When the branching angle is 60°, the length ratio is 2, and the position length is 0, the Y-shaped fin can achieve the best temperature uniformity inside the cavity. By coupling Y-shaped fins with PCMs for PV cell cooling, this research aims to address practical application challenges such as uneven melting, internal temperature stratification, excessive local temperatures, and hotspots caused by the poor thermal conductivity of PCMs.

Ammonia-coal co-firing is one of the important ways to achieve carbon reduction of coal-fired thermal power units, but the research on high proportion ammonia co-firing is rare. In order to further explore the feasibility of high-proportion ammonia co-firing, the mechanism model of ammonia-coal co-firing is established, and the ammonia-coal co-firing and pure ammonia combustion process of 4 MW boiler is simulated by using computational fluid dynamics (CFD) method. The error between CFD calculation results and experimental data is less than 3%. The experimental results show that, when ammonia is co-fired with coal, the flame temperature decreases by about 30 ℃ and the carbon dioxide volume fraction decreases by about 20% for every 20% increase in the co-firing ratio. When the ammonia co-firing ratio is increased from 0 to 40%, the NO volume fraction at the furnace outlet increases by about 77.33%, and the carbon content in fly ash increases from 4.65% to 6.16%; when it is increased from 0 to 60%, the NO volume fraction increases by about 136.44%. When excess air ratio of ammonia-coal co-firing is 1.15, the fuel burnout and nitrogen oxide generation are optimized. The two-stage input of ammonia fuel can reduce the NO volume fraction at the furnace outlet by 31.07% compared with the ungraded input. Compared with the combustion flame of coal combustion and ammonia-coal co-firing, the flame temperature of pure ammonia combustion is lower, the ignition distance is longer and the tangent circle diameter is larger. When pure ammonia is fired, the NO mass concentration at the furnace outlet is 475 mg/m³, and the escaping ammonia concentration is close to 0.

Micro-nano particle doping is an important method for the modification of molten salt thermal storage materials. By taking a binary carbonate molten salt mixture of 40Li₂CO₃-60Na₂CO₃ (mass fraction) as the base molten salt, CuO and CuCl₂ as the dopants, three composite molten salt phase change thermal storage materials, namely CuO-Li₂CO₃-Na₂CO₃, CuCl₂-Li₂CO₃-Na₂CO₃, and CuO-CuCl₂-Li₂CO₃-Na₂CO₃, were re prepared separately using a high-temperature melting method. Moreover, the thermal properties of these compounds were tested, and the effects of additives on the modification of binary carbonate molten salts and composite molten salt phase change thermal storage materials were investigated. The results show that, the melting point of the Li₂CO₃-Na₂CO₃ molten salt with 0.24% CuO addition decreased by 5.2 ℃, the latent heat of phase change decreased by 98.1 J/g, the average specific heat capacity of the solid phase decreased by 0.39 J/(g·℃), and the average specific heat capacity of the liquid phase decreased by 0.77 J/(g·℃). The upper limit of the operating temperature increased by 4 ℃. For the Li₂CO₃-Na₂CO₃-CuCl₂ molten salt with 0.06% CuO addition, the melting point increased by 9.6 ℃, the latent heat of phase change decreased by 15 J/g, the average specific heat capacity of the solid phase increased by 0.07 J/(g·℃), and the average specific heat capacity of the liquid phase increased by 0.12 J/(g·℃). The upper limit of the operating temperature increased by 17 ℃. Both molten salts exhibited improved thermal conductivity performance after the addition of CuO.

To study the effect of inlet temperature and flow step changes on dynamic performance of supercritical carbon dioxide (S-CO₂)/lead-bismuth coupled heat exchanger, a segmental model was established for numerical simulations. Based on the simulation results, a transfer function model was developed and validated to quantitatively assess the effect of inlet step disturbances on the cold-side outlet temperature. The results show that, under inlet temperature step disturbances, the heat exchanger responds quickly, but the temperature field changes with a smaller amplitude. The time constant for the temperature step change at the hot-side inlet is 22.1 s. When the cold-side inlet temperature decreases by 50 K, the temperature at the midpoint of the heat exchanger only drops from 795.23 K to 793.17 K. Under flow step disturbances, the heat exchanger responds with a delay, but the temperature field changes with a larger amplitude. The time constant for the cold-side inlet flow step change is 30.08 s. When the cold-side flow increases to 0.002 kg/s, the temperature at the midpoint of the heat exchanger drops from 795.23 K to 779.08 K. The transfer function established in this study shows good agreement with the results from the segmental model. The findings provide useful insights for the operational strategy of intermediate heat exchangers in the S-CO₂ power cycle and the lead-bismuth fast reactor coupling system.

In the context of building a new type of power system with new energy as the main body, it is required that thermal power units undertake more peak shaving tasks, and coupling heat storage tanks is one of the effective ways for units to improve the peak shaving capability. In order to solve the operation scheduling problem of heat storage tanks and units in the context of peak shaving auxiliary service market, thermal system simulation is conducted on combined heat and power (CHP) units to obtain coal consumption and operational safety zones that reflect the actual operating conditions of the units. After that, an optimization model for the CHP system coupled with heat storage tank is established. Aiming to maximize the net profit of the system, this article intelligently optimizes the hourly operation scheduling of a certain CHP and heat storage tank. The results show that, the heat storage process of the thermal storage tank occurs during the electricity price period, and the heat release process varies depending on the heating load. During the high cold period with high heat load, heat is only released during the electricity price valley period, while during the early and late stages with low heat load, heat is released during the valley and peak periods. The net income of the system decreases with the increase of heating load. Running the entire heating season with the optimized scheduling in this article can increase revenue by 21.13 million yuan per year, with a static investment payback period of 5.22 years.

In order to study the effect of molten salt thermal storage schemes on peak shaving capacity and economy of double reheat condensing units, by taking a 660 MW double reheat condensing unit as an example, seven bypass thermal storage schemes are designed by combing thermal storage with bypass system, considering different thermal storage sources. Through simulation, the changes in indicators of different schemes, such as the minimum power generation load rate, thermal storage load reduction number, compensation for increased peak shaving capacity and coal consumption costs, are studied in the heat storage initial range from 30%THA to 50%THA. The results show that, the minimum power generation load rate of the schemes with multiple parallel heat storage sources are lower than that of the schemes using a single heat source. Scheme VII with three parallel heat storage sources can reduce the minimum power generation load rate to below 18% under different initial heat storage conditions. However, in the Scheme I with superheated steam heat storage, the load reduction number of heat storage exceeds 2.00, and the load reduction capacity per unit of heat storage power is the largest. As the load rate of the initial heat storage condition decreases, there is a maximum compensation for the annual increase in peak shaving capacity, and the compensation for multiple thermal storage heat source schemes is greater than that for a single heat source scheme. The annual increase in coal consumption cost of the scheme including low-pressure bypass heat storage is much higher than other schemes, but it will decrease with the initial working condition of heat storage.

With the grid-connection of renewable energy systems, more coal-fired units are required to participate in deep-peak-shaving and quickly respond to the automatic generation control command. Therefore, the controllers of coal-fired units should not only have satisfactory dynamic performance but also have strong robustness. However, the tuning of proportional-integral (PI) controllers which are widely applied to coal-fire units usually takes the dynamic performance into account and robustness in the application of PI controller parameter tuning is lack. Thus, the maximum-sensitivity-constrained desired dynamic equation (DDE) PI is proposed to obtain good dynamic performance and strong robustness. Simulations and field tests on the hot primary air system of the coal pulverizer indicate that, the proposed control method has better disturbance rejection performance and stronger robustness, which can effectively handle with uncertainties caused by the wide load variation of the unit.

The early faults of sliding bearings are highly concealed. To accurately predict their vibration amplitude, a deep learning model incorporating a YOLOv8-optimized CBAM attention mechanism is proposed. The CBAM module is embedded between the Backbone and Neck to enhance the model’s focus on critical vibration features. Additionally, an improved complete intersection over union loss function is employed to enhance object detection accuracy. Considering the nonlinear and non-stationary characteristics of vibration data, the empirical mode decomposition (EMD) method is integrated into the model to improve the accuracy of vibration state prediction. The experimental results show that, on the 600 MW steam turbine operation dataset, this method improves the detection accuracy by 2.85 percentage points and 8.50 percentage points compared with that of the conventional YOLOv8 and YOLOv7, respectively. Moreover, the root mean square error (RMSE) is reduces, and the mean absolute error (MAE) decreases. Furthermore, in high-noise environments, the model’s error fluctuation reduces by 30% compared with that of the conventional methods, demonstrating stronger generalization ability and stability.

With the increasing demand for flexible operation of power plant boilers, frequent variable-load operation leads to a wide range of fluctuations in pollutant concentrations and flue gas parameters. Modeling of key indicators such as single pollutant or flue gas parameter can no longer meet the actual demand, so it is necessary to consider the coupling of multiple key indicators for synergistic predictive modeling. Based on the historical operation data of coal-fired power plants, feature extraction is performed through kernel function mapping, and a long short-term memory neural network with a hard parameter sharing structure is constructed for multi task prediction modeling. The prediction model is optimized using uncertainty loss methods. The experimental results show that, the proposed prediction model exhibits high prediction accuracy under variable load conditions, and the prediction errors for the key metrics involved in this study are reduced by 25.5%, 41.8% and 4.7%, respectively. The proposed method is capable of predicting several key indicators of utility boilers under variable load conditions, which can assist power plants to achieve pollution control and optimize the thermal efficiency of combustion, and provide technical support for intelligent operation of power plants.

To solve the problem of severe ash accumulation and slagging on heating surface of boilers caused by a large proportion of blended economic coal, based on the close relationship between the ash fouling layer and the flue gas flow field parameters, the concept of cross-sectional “ash fouling characteristic field” is proposed, and a new intelligent soot blowing control system for boilers is developed, which includes functions such as characteristic field detection and generation, and benchmark field prediction. By comparing the difference in “drop value” and “concentration” between the benchmark feature field and the current feature field, the system can timely and accurately determine the appropriate blowing time, achieving “intelligent perception and on-demand blowing”. The new system solves the problem of lack of measurement points and low accuracy in existing model calculation methods, overcomes the disadvantage of high equipment cost in furnace observation methods, and uses on-site full section data collectors combined with intelligent prediction models for ash pollution characteristic fields to achieve low-cost and high-precision detection of ash and slag accumulation, effectively solving the problems of over blowing and under blowing. The actual application effect of the power plant shows that, after the new system was put into use for 3 months, the monthly blowing frequency decreased by 19.6%, and the monthly blowing steam consumption decreased by 229.0 tons, which is equivalent to a direct economic benefit of 284 000 yuan per year. In addition, the system also brings multiple indirect benefits, such as avoiding sudden coking that causes the unit to stop, extending the service life of the heating surface, and avoiding delayed soot blowing that leads to a decrease in boiler efficiency. The relevant control optimization experience can be used as a reference for similar units in the future.

The porous media methodology is used to describe the filter bags and their surface ash layer seepage flow. On this basis, the discrete particle model (DPM), as implemented in Fluent software, is employed to simulate the dynamics of dust particles movement and deposition in a baghouse filter. The effects of dust particle size on evolving morphology of the cake on the filter bags are investigated, and the influence of additional resistance of the filter cake on subsequent ash particle deposition is explored. The results show that, when the duration of dust removal is sufficiently long, the cake thickness and pressure loss in the baghouse filter increase in a linear fashion over time. For a constant dust mass flow rate, the pressure loss becomes higher with smaller dust particles. The smaller ash particles are transported more effectively by the upward airflow to the top of the vertical filter bag, whereas the larger particles, due to their weight, tend to settle in the middle area. This results in significant differences in the distribution of cake thickness. In contrast to conventional algorithms that neglect cake resistance, the proposed model, which incorporates this resistance through advanced development in commercial software, predicts a more uniform distribution of dust thickness, which is more consistent with the actual situations. This conclusion can provide references for improving the operational efficiency of baghouse filters.

To enhance the cybersecurity protection capabilities of power monitoring systems, a security reinforcement middleware for interal unidirectional safety isolating device for electric power has been designed. This middleware integrates compatibility adaptation, file format correction, encryption authentication, load balancing, and access control functions, addressing the security issues such as business system compatibility, hardware failures, and plaintext communication faced by isolation devices during the upgrading and reinforcement process. It enhances the security control of data transmission channels in power monitoring systems and achieves an “efficient and unobtrusive” and “standardized” security upgrade and reinforcement of the isolation devices. This middleware has been successfully applied to all thermal power, hydropower, and new energy power stations of Huaneng Group, strengthening the cybersecurity boundary protection capabilities of critical information infrastructure in power monitoring and ensuring the information security of power production.