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.

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.

Currently, the centralized optimization regulation strategy for conventional energy storage systems struggles to meet the operational requirements of centralized-distributed energy storage systems in rural areas. To address this challenge, this study examines a typical village in the Central Shaanxi Plain, Shaanxi Province, China, and integrates the usage patterns of agricultural machinery batteries into energy storage regulation. A peer-to-peer （P2P） trading mechanism for distributed energy storage, based on a combinatorial double auction, is proposed. In the trading environment, a double-layer optimal regulation model for rural centralized-distributed energy storage systems is established using a Stackelberg game approach and computationally solves it. The results show that 1）P2P trading are highly influenced by agricultural production patterns in both quantity and time. 2）P2P trading reduces the operating cost of each subject in the centralized-distributed energy storage system by 4.96%, reduces carbon emissions by 10.41%, and increases the PV consumption rate by 18.04%. 3）The annual electricity cost of different types of rural households is reduced by the increase of decentralized energy storage capacity, the reduction is more significant after the introduction of P2P trading, and the cost reduction is especially prominent for rural households with large rooftop PV installations, small electricity demand, and sufficient energy storage resources. Energy storage operator will suffer from the increase in revenue due to the increase in decentralized energy storage capacity, and the revenue will be further reduced after the introduction of P2P trading, but can be compensated for by appropriately charging operation and management fees.

To address the operational instability of the geothermal reheated dual-pressure organic Rankine cycle （R-DPORC） system caused by transient fluctuations in cold/heat sources, this study proposes two targeted control strategies： constant-load control and variable-load control. A dynamic simulation model of the R-DPORC system has been developed using Matlab/Simscape to analyze its dynamic response characteristics under varying cold/heat source conditions and load changes. The variations in system efficiency, degree of superheat, pressure, and mass flow rate are investigated. Results indicate that regulating the flow rate of working fluid pump is a critical method for achieving dynamic control of the R-DPORC system. Depending on specific operational scenarios, different operating modes can be flexibly combined. Through adjustments, the system can gradually achieve a new stable state and meet output requirements. Moreover, the optimized control strategy significantly improves the dynamic adaptability of the system under complex operating conditions, ensuring long-term stable operation and higher energy efficiency.

Focusing on the optimization of the spacing parameters of a dual-float wave energy conversion （WEC） device, systematically investigating the influence of the wavelength-to-float spacing ratio on the energy harvesting performance and hinge loads under both regular and irregular wave conditions. Through the application of numerical simulation and model trial methods, the working mechanism of the wavelength-to-float spacing ratio on system performance is revealed. The findings indicate that under regular wave conditions, the energy harvesting width ratio of the system exhibits a significant wavelength dependency, reaching a peak value of 0.44 when the wavelength-to-float spacing ratio is 0.25, which is a 46.1% increase compared to the case with a ratio of 0.063. Under irregular wave conditions, appropriately adjusting the float spacing can reduce the horizontal hinge load at the connection joint by approximately 75% and the vertical hinge load by about 25%, thereby effectively enhancing the service life of the device. Oblique incident waves induce a nonlinear response in energy harvesting width ratio, and the system achieves the optimal energy harvesting width ratio when the incident angle is 15°, which is a 22% improvement compared to the case of vertical incidence.

Taking a large public building in a hot summer and cold winter area as the research object, a simulation model of shallow medium deep geothermal cascade utilization coupled heating was built based on TRNSYS software. The operating characteristics of the shallow medium deep coupled heating system during the heating season were analyzed and compared with a single medium deep geothermal cascade utilization heating system and a shallow ground source heat pump system. The results show that the coupled system is superior to a single deep or shallow geothermal heating system in terms of end heat transfer, geothermal return water temperature, heat pump unit COP, and system energy utilization efficiency. The system is more stable and adaptable. The average energy utilization efficiency of the system reaches 0.95, verifying the feasibility of the coupled system operation.

Taking a horizontal pendulum wave energy converter （WEC） based on a spiral spring-flywheel power take-off （PTO） system as research object, considering the spring stiffness and flywheel moment of inertia as variables, a fully coupled numerical model of the WEC is constructed to investigate energy acquisition under multiple degrees of freedom through model test and numerical simulation. The research shows that installing a spiral spring-flywheel PTO can enhance the stability of energy acquisition and increase the power generation bandwidth of the WEC. Under regular wave conditions, the standard deviation of power is positively correlated with the spring stiffness and negatively correlated with the flywheel moment of inertia, with this phenomenon being more pronounced near the resonance period.

A power smoothing strategy without energy storage system by utilizing the large rotational inertia of the wind turbine rotor to achieve power smoothing is proposed to solve the problem of output power fluctuations of modern large-scale wind turbines under rated wind speed. Firstly, the inherent characteristics of the wind turbines are employed to provide an immediate and accurate equivalent wind speed for control participation. Secondly, the upper and lower limits of the rotational speed are set for each wind speed segment based on high aerodynamic efficiency zone and wide speed-ratio design, and the entire inertia control process is given simultaneously to achieve the energy storage and release of the wind turbine rotor. Subsequently, multiple prediction models based on the slope of the wind speed pulsation trend are constructed via big data sources to realize the predictive action of the torque. Finally, the comparative simulation experiments of the power output of the wind turbine are carried out by BLADED simulation software and a certain actual wind farm. The results show that the adopted strategy stabilizes the output power effectively without the additional energy storage devices.

It is of great significance to realize transient stability evaluation accurately and quickly for stable and safe operation of power system. Aiming at the problem of low prediction accuracy in the current transient stability evaluation of grid-connected photovoltaic energy storage systems, a transient stability evaluation method based on integrated deep Random forest algorithm （gcForest-AdaBoost） is proposed by combining deep learning and ensemble learning techniques. Firstly, the initial input features are constructed according to the steady-state components of the grid-connected photovoltaic energy storage system during operation. Secondly, in order to reduce the overfit of the model and ensure that the model still has strong learning ability after the number of cascades increases, a transient stability evaluation method based on gcForest-AdaBoost is proposed by combining deep random forest algorithm and AdaBoost algorithm. Thirdly, the gcForest-AdaBoost model is trained with input feature set, and the transient stability evaluation model of grid-connected PV energy storage system is established. Finally, the IEEE 39-node system is connected to the photovoltaic energy storage unit to build a case system for simulation analysis and data acquisition, and the evaluation results are obtained. Numerical examples show that the proposed model can effectively analyze the transient stability of grid-connected photovoltaic energy storage systems, and it is found that the proposed model has good robustness and generalization ability.

An integrated energy system coupled with solar energy and biogas is designed in this study, and a joint optimization method of capacity and operation is proposed. Firstly, a thermodynamic model of biogas production is introduced, and a capacity-operation two-layer optimization model is constructed. The upper layer optimizes the size of the biogas digester and the capacity of energy conversion and energy storage equipment to minimize the annual total cost. The lower layer takes the upper-layer results as constraints to optimize the operation plan of energy conversion and energy storage equipment, minimizing the operation cost. Secondly, by integrating the nonlinear programming method into the genetic algorithm, the model is solved to determine the optimal capacity configuration and operation scheme of the system. Finally, five simulation scenarios are used to verify the effectiveness of the proposed system and the joint optimization method. The results show that the integrated energy system optimized by the proposed method has the best economic performance, and the energy consumption scheme is efficient and reasonable.