This paper explores the effects of attaching radiative cooling films at different positions of solar cells in different seasons on their thermoelectric performance through experiments and simulations. The results show that attaching a radiative cooling film on the front side can significantly reduce temperature, but due to the decrease in transmittance, the electrical performance is lost by nearly 70%; while attaching a film on the back side can reduce the average temperature by 5.08 ℃ in summer, and the power is approximately increased by 2%, maintaining a high photoelectric conversion efficiency while effectively reducing the module temperature, In terms of the comprehensive performance of thermal management and power generation efficiency, it performs even better. In summer, the film on the back side has a good cooling effect, and in a low-temperature environment with an average ambient temperature of -10 ℃ in winter, the temperature difference of the module decreases by 0.59 ℃. By reducing the temperature difference, the service life can be extended. At the same time, the radiative cooling effect is affected by irradiance, ambient temperature and wind speed. The cooling effect of attaching a film is more prominent under high temperature and high irradiance conditions, while enhancing convection will weaken its cooling effect.

To address the problem of poor voltage stability of wind-solar-energy storage DC microgrids in distributed renewable energy systems, an optimized nonlinear active disturbance rejection control strategy based on the SAC algorithm （SAC-ADRC） is proposed. Firstly, the wind-solar-energy storage system is modeled with nonlinear ADRC control. Then, the gain parameters of the nonlinear ADRC are reconstructed by using linear/nonlinear ADRC switching to improve its internal parameters which are more difficult to tune and analyze. Finally, the analysis establishes a mechanism for SAC intelligence to learn interactively with the microgrid environment, enabling the adjustment of non-linear ADRC parameters. Comparative analysis using algorithm convergence curves and simulation of various classical working conditions confirms the superiority of the SAC-ADRC control strategy in terms of interference performance. Thus, it is shown that the organic integration of nonlinear ADRC and deep reinforcement learning improves the stability of the microgrid bus voltage.

In this paper, the optimization strategy of reserve capacity and cost sharing mechanism are studied considering the source-load uncertainty. The probability distribution model of wind and PV forecast deviation is improved based on Gauss-Laplace distribution, and an improved Latin hypercube sampling method is proposed based on Box-Muller transformation to promote the efficiency and accuracy. And then a reserve capacity optimization model is constructed to minimize the cost considering the constraints of condition risk. Finally, a reserve cost sharing mechanism is established with the objective of achieving Maxmin fairness in the allocation utility value and the constraint interval of cost allocation as the constraint condition. The IEEE-30 standard test cases show that the improved Latin hypercube sampling method can effectively improve the sampling efficiency and reduce the computation time, and the benefit sharing is more reasonable based on the proposed strategy, which can more effectively motivate the demand side to participate in the standby market.

To investigate the dynamic response of the multi-bucket jacket foundation of offshore wind turbines under storm surge load, this paper conducts a series of 1 g model tests using the motor servo random dynamic loading equipment. Then, the influence of different depth-to-diameter ratios of the suction bucket on the soil and structure is further investigated through numerical simulations. The results indicate that the extreme horizontal displacement of the structure rises as wind speed increases under storm surge conditions, and the amplification coefficient of horizontal displacement follows a trend of “increasing initially before decreasing”. The peak value of the Fourier amplitude spectrum for the nacelle position acceleration increases with the load, while the peak frequency exhibits a pattern of “decreasing first and then increasing”. As the depth-to-diameter ratio of the suction bucket increases, both the extreme horizontal displacement and the amplification of the structures coefficient corresponding decrease. A depth-to-diameter ratio of L/D= 0.5 is the least favorable, as it cannot withstand storm surge loads. The difference between depth-to-diameter ratios of 1.0 and 1.5 is negligible. Taking into account reliability and economy, a depth-to-diameter ratio of 1.0 is the optimal type. Different depth-to-diameter ratios also have the influence onthe rotation center of the SBJ foundation.

Adopting the CEL finite element method to systematically simulate the penetration process of rectangular spudcan foundations under typical offshore wind geological conditions. Based on simulation results, the extent of plastically strained soil around the foundation is quantified, soil softening zones are identified, and corresponding strength reduction factors are calculated. Subsequently, small-strain finite element model incorporating these softening parameters are developed to calculate directional stiffness reduction coefficient η. Comparative analyses with non-softening reference models reveal the substantial influence of soil strength degradation on foundation stiffness. A comprehensive parametric study further evaluates the sensitivity of stiffness characteristics to two critical geotechnical parameters： the normalized shear stiffness ratio Gmax/su and the critical shear strain at failure γfp. Results demonstrate that：1） Soil softening effects varies with different directional in-situ stiffness components, but the extent cannot be neglected; 2） Stiffness reduction coefficients exhibits consistent decreasing trend with increasing level of loading;3） Stiffness increases with higher Gmax/su, but decrease with larger γfp.

A fault diagnosis method for wind turbine rolling bearings is proposed, which combines the gradient dynamic selective alignment （DSA） method, dual-channel feature fusion technique （DCFF）, and deep learning. Firstly, the acquired one-dimensional time series data are transformed into two different two-dimensional image representations using recursive mapping （RP） and Markov transfer field （MTF）. These transformed images are then input into an encoder for reconstruction into a low-dimensional representation. Next, a dual-channel feature fusion convolutional neural network （DCFFC） is constructed, embedding an improved attention mechanism within FRNet to extract in-depth feature information. A second-level feature fusion is performed to complete the feature classification. Finally, a gradient masking matrix is constructed using the data reconstruction loss of the decoder and the feature extraction network classification loss to achieve gradient dynamic self-adaptation throughout the fault diagnosis process. Experimental validation using the Paderborn dataset demonstrates that the proposed method achieves a diagnostic accuracy of 99%, effectively extracting fault-specific diagnostic information.

This study employed FLACS software to simulate hydrogen leakage scenarios involving a Toyota Mirai Gen II fuel cell vehicle in underground parking garages, to systematically investigate the impacts of ventilation scheme, vent orientation, and ventilation rate. Results indicate that the combined action of the suspended ceiling and ventilation system completely removes the flammable gas clouds, achieving the highest hydrogen removal efficiency. Upward-exhaust ventilation is more effective than other orientations. At a ventilation rate of 24 air changes per hour （ACH）, the peak equivalent stoichiometric cloud volume is 22.5% lower than that for no ventilation, and the cloud removal time is 43.4% shorter than that at 12 ACH. Further increases in ventilation rate provide limited enhancement in flammable cloud evacuation efficiency.

To investigate the wind uplift resistance and failure modes of rigidly supported clamp-fixed photovoltaic （PV） modules, considering the effect of module fixation spacing and frame height, this study conducted wind uplift resistance tests on PV modules with different parameter combinations. The entire loading process of the PV modules under simulated wind load was measured, including displacement and strain changes. The damage deformation characteristics and failure modes of the PV module were analyzed. A numerical analysis model of the PV module was established using the structural finite element analysis software ABAQUS to further study the factors affecting the wind uplift resistance of the PV modules. The results show that the wind uplift failure mode of the PV module is the failure of the engagement between the fixed block and the module frame, leading to the entire PV module being uplifted. The wind uplift failure criterion for the PV module is defined as failure occurring when the slippage between the clamps and the PV module exceeds 2/3 of the original constraint surface section length of the block on the module frame. Reducing the length and width of the PV module, and increasing the height and fixation spacing of the PV module, can effectively improve its wind uplift resistance, with reducing the module width having the most significant effect.

In order to achieve the recycling of nutrients in photo-fermentation hydrogen production tailing liquid, the adsorption capacity of zeolite on NH₄⁺ and K⁺ in photo-fermentation hydrogen production tailing liquid was investigated using natural zeolite as adsorbent and kinetic and thermodynamic analyses were carried out. It is found that the adsorption of zeolite on NH₄⁺ and K⁺ in photo-fermentation hydrogen production tailing liquid exhibites a tendency of accelerated adsorption, then gradually reaches balance, which is attained at 2 h and 3 h of adsorption, respectively. When adsorption time is 2h and adsorption temperature is 35 ℃, zeolite demonstrates stronger adsorption capacity for NH₄⁺ with an adsorption of 1.82 mg/g. When adsorption time is 3 h and adsorption temperature is 45 ℃, zeolite exhibites its maximum adsorption capacity for K⁺, reaching 7.11 mg/g. The quasi-secondary kinetic model provides a superior description for the adsorption process. The adsorption process of zeolite on NH₄⁺ and K⁺ in the tailing liquid of photo-fermentation hydrogen production is non-spontaneous. The adsorption of NH₄⁺ by zeolite is characterised as an exothermic entropy reduction reaction, while the adsorption of K⁺ is identified as an adsorptive entropy increase reaction.

In order to reduce the wake loss in the wind farm and enhance the whole field power generation, the whole field cooperative control based on yaw control has become a current research hotspot. To address issues such as existing studies not fully considering the dynamic changes in incoming flow and the time-lag effects of wind farm flow, a high-fidelity large eddy simulation method is used to numerically simulate the wind farm flow, and the flow delay time between units is determined by the spatial and temporal correlation between the flow field and the power of the neighboring units. Considering the flow delay time of the flow field, a dynamic yaw control strategy is proposed for the wind turbine under the turbulent inflow conditions. The large eddy simulation results show that the total power generation of the wind turbine array under static yaw and optimal dynamic yaw control is increased by 11.5% and 12.5%, respectively, compared with that under no yaw control. Compared to the static yaw control, the wake development between the wind turbine array is more fully developed and the wake velocity recovery is faster under dynamic yaw control.