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.

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.

The issue of wind turbine icing under the mixed-phase of ice crystals and supercooled water droplets is studied. The mechanism of wind turbine mixed-phase icing is analyzed, and the numerical simulation of airfoil icing on wind turbines is carried out. A particle motion trajectory equation is established using the Lagrangian method. The solution method for the control equation and the relevant definition of the collection coefficient are provided. A new mathematical model for icing under mixed-phase conditions is proposed, and the mass and energy conservation equations for liquid water on the surface of a wind turbine airfoil under mixed-phase conditions are established. The mathematical expressions for each equation are provided, and the physical phenomena of ice crystal adhesion and erosion are analyzed. The solution method for the icing growth model is provided. The accuracy of the icing model method proposed in this paper is demonstrated through comparison with experimental results. The icing characteristics of wind turbine airfoil surfaces under mixed-phase conditions are studied, and the impact of various initial parameters on icing characteristics is investigated. The research results indicate that erosion phenomena can affect surface icing. As the erosion rate increases, the surface icing decreases. The higher the adhesion coefficient and melting ratio, the greater the amount of icing. Different temperatures can lead to the formation of various ice forms on the airfoil. Rime ice forms at higher temperatures, while glaze ice forms at lower temperatures. However, with the increase in ice crystal content and diameter, the range and amount of icing change less. The research work provides a foundation for further research on wind turbine icing under mixed-phase icing conditions and the design of anti-icing and de-icing systems.

To reduce the weight of large wind turbines, structural stiffness is often compromised, leading to local buckling instability and trailing edge structural damage in composite blades under large-scale deformation. To address this issue, this paper introduces an inner rib structure for wind turbine blades to examine its effectiveness in improving resistance to buckling-induced damage. Structural damage response analysis was conducted using the explicit dynamic method under ultimate load conditions at extreme wind speeds and three yaw angles. The results indicate that trailing edge damage in blades is primarily a buckling-driven process, with significant trailing edge buckling occurring only when bending moment loads are applied at specific angles. The support provided by the inner rib in bionic blades localises damage to the transition section, effectively preventing its progression to the blade root section. Under tensile loads, damage concentrates in the trailing edge of the transition section, whereas under compressive loads, damage propagates laterally along the main beam. The buckling resistance of composite layers varies with ply angles, resulting in distinct damage patterns.

To mitigate the risk to secure and adequate operation of power systems under storm conditions, this paper proposes a synergistic control decision-making method aimed at enhancing adequacy and power angle stability. Firstly, the output from wind farms outside storm-affected areas is predicted using the Informer model, providing input for subsequent optimization models. Secondly, based on a “decoupling optimization, aggregation and coordination” strategy, the method decouples system adequacy optimization from power angle stabilization control. For adequacy optimization, operational risk costs are reduced by scheduling adjustable resources. For power angle stabilization, the extended equal-area criterion quantifies the transient stability margin, and preventive-emergency control synergy is applied for each fault scenario to ensure stability. A two-layer optimization model is then constructed and solved iteratively. Finally, case studies on a modified IEEE 39-node system demonstrate the benefits of the proposed model in reducing system load loss and enhancing grid security.

By improving the forecasting accuracy of model products through wind speed deviation correction methods, reliable data support is provided for wind power generation forecasting in wind farms. Taking the Lingchuan County Wind Farm in Shanxi Province as an example, three machine learning methods recurrent neural network （RNN）, nonlinear model（NLinear）, and Transformer were employed to establish wind speed deviation correction models for CMA-WSP2.0 model products. The results show that the results of three methods are better than that of the original model products, and Transformer and NLinear perform better in improving the accuracy of wind speed at heights of 10 m meters and 100 m meters, respectively. Therefore, machine learning methods can effectively improve the quality and reliability of wind speed data, offering a more accurate data foundation for wind energy resource development and utilization, power forecasting and other fields.

In order to address the problem of high slagging rate of corn straw combustion, mixing oil pine with less slagging feature and corn straw to produce the mixture combustion, using thermogravimetric analysis, SEM scanning and energy spectrometry, the effect of oil pine on the combustion characteristics of corn straw and slagging characteristics is studied. The results show that: there is a certain interaction during the combustion process of the oil pine-corn straw mixed fuel. As the temperature rises, it changes from inhibitory effect to synergistic effect, and then from strong synergistic effect to weak synergistic effect. When the mixing ratio of corn straw and oil pine is 4:6, the overall combustion characteristics are the best, the combustion temperature increases to 475.6 ℃, the stable combustion index increases to 8.9379×10^-6 mg/（K²·min） and the combined combustion characteristics index increases to 0.0929×10^-8 mg²/（K³·min²）, and the slagging rate decreases from 56.25% to 9.87% with the blower strength of 0.1 m/s, the slagging rate decreases by 82.45%, and the content of Si and Na, K alkali metal elements in the ash decreases from 46.42% to 29.93%. The addition of oil pine can significantly enhance the combustion characteristics of corn straw and effectively reduce the slagging rate.

The project boundary,baseline emissions and project emissions of fuel ethanol projects were defined. The greenhouse gas （GHG） emission of 3 generations of bioethanol projects,including corn liquid fermentation,sweet sorghum solid fermentation and cellulose hydrolysis fermentation were analyzed. By introducing a secondary emission reduction accounting system for the resource utilization of by-products, the maximum carbon emission reduction potential of each generation of bioethanol processes was systematically revealed. The results show that the sweet sorghum solid-state fermentation has the highest carbon emission reduction potential, with the maximum theoretical 5.14 ton CO₂e GHG abatement per ton of ethanol production. Cellulosic ethanol has greater carbon negative potential under the background of technological progress.

In this paper, MCM-41 mesoporous molecular sieve catalysts modified by Cu, Fe, Co and Ni elements were prepared by impregnation method. XRD and BET characterization analyses were carried out on the modified catalysts to explore the physicochemical structures and other characteristics of catalysts modified by different metals.The effects of co-pyrolysis of cellulose, lignin and polypropylene （PP） on the synergistic reaction and the distribution of pyrolysis products were investigated by TG-FTIR and Py-GC/MS. The results show that MCM-41 can promote the reaction between biomass and PP, and the yields of aromatics and light hydrocarbons are increased. Compared with MCM-41, modified MCM-41 can promote the precipitation of light olefins, C₅~C₁₁ aliphatic hydrocarbons and aromatics. Cu, Fe and Co modification can promote the formation of monocyclic aromatics. Compared with MCM-41, MP-M/Fe has the highest proportion of olefin precipitation, reaching 59.68%, and XP-M/Fe has the highest proportion of light olefin precipitation, reaching 32.84%. XP-M/Co has the highest proportion of alkane precipitation, reaching 34.22%. The proportion of other groups of alkenes and alkanes in the pyrolysis products increases.

Taking the three-dimensional horizontal axis tidal current turbine as the initial model, the influence of the winglet twist angle on the hydrodynamic performance and wake characteristics of the tidal current turbine is analyzed by CFD numerical calculation, and the influence mechanism of the winglet's twist angle on the hydrodynamic performance of the turbine blade is clarified. The results show that the change of the winglet twist angle has a significant impact on the hydrodynamic performance of the tidal current turbine. Compared with the initial model, when winglet twist angle is -6°, the power coefficient of the tidal current turbine increases by 5.17% and the drag coefficient increases by 7.01%. In the range of twist angle from -9° to 6°, the power coefficient with winglet first increases and then decreases with the increase of twist angle, while the drag coefficient decreases monotonously. The changes of the winglet twist angle significantly affect the radial flow state of the fluid immediate behind the blade tip of the turbine, affect the tip loss and the surface pressure distribution, and then change the hydrodynamic performance of the tidal current turbine. By comparing the power spectrum density curve of velocity fluctuation, it can be seen that the winglet's twist angle will affect the axial velocity fluctuation of blade tip vortex, and the influence will gradually decrease with the increase of axial distance, but the influence on radial velocity fluctuation is not obvious.