Molten salt thermal energy storage technology can improve the flexibility of thermal power units. The molten salt evaporator, a core component of the system, utilizes the thermal energy of molten salt to convert boiler feedwater into superheated steam. However, the unique thermophysical properties of molten salt and the complex structure of the heat exchanger render existing heat transfer correlations inadequate for accurately predicting its thermal performance. Experimental studies on molten salt heat exchangers are costly, while existing numerical simulations cannot achieve coupled heat transfer calculations between the single-phase molten salt side and the phase-change working fluid side. In this study, with given feedwater inlet parameters, a numerical model for the molten salt side heat transfer is established by assuming an initial enthalpy distribution along the flow path. The heat flux distribution obtained from the simulation is then used to calculate the enthalpy variation of the working fluid, which is iteratively compared and corrected against the initially assumed values. Through multiple iterations, an accurate computation of the heat transfer process in the molten salt steam generator is achieved, enabling a detailed investigation of its operational characteristics. The results indicate that at an operating pressure of 2 MPa, during the transition from subcooled water to complete vaporization, the vaporization rate gradually increases. The heat flux peaks at 86 295.12 W/m² upon complete vaporization, then decreases rapidly and eventually stabilizes around 5 000 W/m². Significant temperature non-uniformity is observed across the flow cross-section of the molten salt, with a maximum thermal deviation of 216%. This temperature non-uniformity is alleviated as the inlet molten salt temperature decreases.

The utilization of industrial solid waste for thermal energy storage represents an innovative approach to address environmental challenges while advancing energy storage technologies. This study comprehensively examines the potential of industrial solid wastes, including coal fly ash, red mud, sewage sludge, gypsum, metallurgical slag, and waste concrete, as composite thermal energy storage materials. The discussion encompasses the material properties, preparation methods, and applications of industrial solid wastes in composite heat storage systems. The study highlights their capacity for high-temperature stability, enhanced thermal conductivity, and phase change material integration, offering significant energy density improvements. Moreover, the review identifies challenges such as material heterogeneity and long-term thermal cycling performance. Strategies for industrial solid waste modification, encapsulation of phase change materials, and innovative composite designs are analyzed to enhance their applicability in sustainable thermal energy storage systems.

Biomass resources in China are widely distributed and highly abundant, holding great potential for substituting traditional fossil fuels and promoting the achievement of carbon peak and carbon neutrality goals. During storage and transportation, biomass is prone to self-heating. When the accumulated heat raises the internal temperature of biomass to a certain level, chemical reactions will gradually accelerate, leading to biomass self-ignition. In traditional biomass self-ignition studies, thermogravimetric/calorimetric experiments typically employ powdered samples. However, this approach significantly deviates from the actual storage conditions of biomass. Moreover, existing biomass reaction kinetics models exhibit poor adaptability below 250 ℃. To address these issues, a testing platform for the low-temperature pyrolysis and oxidation characteristics of biomass was established. The thermal degradation behavior of rice straw and soybean shell samples with different particle sizes (original large particles, 2.0 mm particles, and 0.2 mm particles) was investigated under various oxygen concentrations. Two kinetic models, namely the pyrolysis-independent component oxidation model and the pyrolysis-lumped oxidation model, were developed and optimized. These models accurately predicted the pyrolysis and oxidation behavior of biomass in the low-temperature range. The results indicated that the reaction rate increased significantly with temperature. However, as biomass consumption progressed, the promoting effect of temperature on the reaction rate gradually diminished. Increasing the oxygen concentration also accelerated the reaction rate, but its impact was weaker than that of temperature elevation. Under the same temperature and oxygen concentration conditions, the 2.0 mm particle samples exhibited the highest reaction rate, while the original samples had the lowest rate, with the 0.2 mm particle samples falling in between. Experiments on biomass samples with original particle sizes and the development of targeted kinetic models are more representative of real-world conditions. The pyrolysis-lumped oxidation model effectively predicted the mass loss behavior of rice straw and soybean shell samples with different particle sizes under various oxygen concentrations as the temperature increased, demonstrating its applicability for predicting low-temperature pyrolysis and oxidation reactions of biomass.

To further improve the cycling performance of the cold storage packed bed for liquid air energy storage systems, a multi-cycle study was conducted on the two-dimensional continuous solid-phase model of the cold storage packed bed using the finite element simulation method. Performance improvement methods for filling phase change materials at the top of a packed bed in two different ways were proposed and analyzed. The influence of the thermal physical properties and filling thickness of different phase change materials on the key parameters of the composite cold storage packed beds was discussed. The results show that both the composite cold storage packed bed and the solid-phase cold storage packed bed have an increase in round-trip efficiency with the cycle times, and tend to a quasi-steady state in the 10th cycle. As the intermediate phase transition temperature of the phase change material increases, the rate of phase transition occurring in the cycle gradually decreases. The composite cold storage packed bed filled with phase change materials with higher intermediate phase change temperature, higher volumetric heat capacity, and higher latent heat of phase change exhibits better performance. Increasing the filling thickness of phase change materials can help further improve the performance of composite cold storage packed beds. The composite cold storage packed bed with the best comprehensive performance shows an increase of 15.2% in cold storage density and 0.22 percentage points in round-trip efficiency compared to the solid phase cold storage packed bed, while the cold storage efficiency only decreases by 1.52 percentage points. The research can provide theoretical guidance for the design of cold storage packed bed systems for large capacity liquid air energy storage.

The oily dust on photovoltaic (PV) modules significantly reduces power generation efficiency, but conventional cleaning agents suffer from poor cleaning performance, cause environmental pollution, and bring component corrosion risks. This study analyzed the dust composition via XRF, XRD, and ignition methods, revealing that organic matters with a mass fraction of 17.52% cause high adhesiveness. An eco-friendly cleaning agent was developed by optimizing the formulation via a four-factor three-level orthogonal experiment using Class A eco-friendly components. Its degradation and corrosion properties were verified through the continuous activated sludge method and immersion experiments. The results showed 10 g/m² oily dust could reduce the PV module power by 30.28%, while the cleaning agent achieved a cleaning efficiency of 99.84% at 30-fold dilution. The cleaning wastewater with a COD of 3 000 mg/L achieved a biodegradability of over 90.41%. Field application on oil plant rooftops restored 79.4% power efficiency and raised surface temperature by 5.6 ℃. Costing only 0.5 yuan per square meter and causing no corrosion to PV modules, the proposed cleaning agent outperforms commercial alternatives. It enables efficient and eco-friendly cleaning, ensuring stable operation of PV power stations and improving power generation efficiency.

To meet the high requirements of selective catalytic reduction (SCR) systems in coal-fired power plants for accurate and low-latency prediction of nitrogen oxides (NO_x) mass concentrations, this study designs and proposes a soft sensing and deployment framework that balances high accuracy and real-time performance. Using more than 110 000 sets of high-dimensional operational data from a 660 MW coal-fired unit, a systematic comparison of deep learning (DL) and XGBoost models was conducted on a unified platform. Time series cross-validation combined with grid search was employed to optimize hyperparameters, and model performance was comprehensively evaluated in terms of predictive accuracy, computational efficiency, and interpretability via local interpretable model-agnostic explanations. On this basis, an “edge-embedded” collaborative deployment strategy was proposed, in which the DL model is deployed on edge servers to deliver high-accuracy predictions, while the XGBoost model is embedded into the distributed control system (DCS) to ensure real-time responsiveness. The results show that the DL model outperforms XGBoost in dynamic response and predictive accuracy, achieving root mean square errors approximately 10% lower than that of the XGBoost, and maintaining stability under highly fluctuating conditions. Variable importance analysis highlights flue gas oxygen content, burner wall temperature, and total air volume as the dominant factors affecting NO_x formation. The proposed collaborative architecture can theoretically achieve millisecond-level inference and provide offline fault tolerance, offering a practical pathway for intelligent ammonia injection control and combustion optimization.