Largescale wind power grid integration increases the uncertainties of system operation. It is urgent to use rapidly adjustable resources to smooth the power imbalance caused by wind power and load fluctuation and consider the impact of spinning reserve calling process on the system power flow. Firstly, the probability distribution model of wind power and load prediction error is analyzed. Then, the optimal dispatching model of power system with N1 network security opportunity constraint and spinning reserve opportunity constraint is established, and the unit output is optimized with the goal of minimizing the total dispatching cost. Finally, the Benders decomposition method based on the identification method of active integer variables is used to deal with the N1 network security constraints to improve the solving efficiency. Using the modified IEEE30node test system, it is verified that the proposed model can guarantee the reserve availability, economy and safety of the system, and fully excavate the fast adjustable capacity of pumped storage.

Ethyl levulinate (EL) is a highly promising biomass fuel and additive, and the production of EL using yieldrich biomass is beneficial to the industrialized largescale production of EL. In this article, we studied the effects of sulfuric acid dosage, reaction time, reaction temperature and substrate concentration on the yield of EL using ultralow concentration sulfuric acid catalyzed cellulose, and optimized the EL production process by using response surface BoxBehnken model to study the effects of various factors on the yield of EL, and obtained the optimal process conditions for EL production from ultralow concentration sulfuric acid catalyzed cellulose: sulfuric acid dosage 0.5%, reaction temperature 204 °C, reaction time 240 min, substrate concentration 29 g/L reaction, the actual average yield of EL was 66.70%, with a relative error of 3.25% from the theoretical prediction. GCMS analyzed the distribution of alcoholysis products of ultralow concentration sulfuric acidcatalyzed cellulose under different reaction times, and proposed possible reaction pathways, the results of which can provide reference and reference for the alcoholysis conversion of cellulosic biomass.

Deep borehole heat exchangers (DBHE) is currently recognized as the most environmentally friendly way to exploit geothermal energy. The deep Ushaped borehole heat exchanger is a new type of DBHE which is being explored. Heat extraction capacity and influence radius are the important problems in the process of popularizing this technology. Based on the measured parameters of ground temperature and thermophysical properties, the heat extraction capacity and influence radius of the 2 500 m deep Ushaped borehole heat exchanger are analyzed by the way of insitu test and numerical simulation in Caotan area of Xi'an. The results show that the sustainable heat extraction power of the heat exchanger in 30 years is closed to 750 kW, with an average linear meter of 144 W; The attenuation degree and range of wall rock temperature increase with the increase of heat extraction power; The influence radius of the deep Ushaped borehole heat exchanger are different at different depths, and the deep stratum is larger than the shallow stratum as a whole; The influence radius of the 2 500 m deep Ushaped borehole heat exchanger with the heat extraction rates of 750 kW can greater than 100 m after work for 30 years, and there is a certain degree of thermal interference between the inlet well and outlet well of the Deep Ushaped borehole exchanger.

In response to the challenge posed by the limited accuracy of traditional fault diagnosis methods in wind turbine gearbox applications due to the complex and variable operational conditions and the presence of significant noise, the MTFSwin Transformer wind turbine gearbox fault diagnosis model is proposed. Initially, the onedimensional vibration time series signal is transformed into a twodimensional feature map with correlated temporal information using the Markov Transition Field (MTF) graph encoding method. Subsequently, this feature map is employed as the input for the Swin Transformer model, which utilizes a selfattention mechanism for automatic feature extraction. This process culminates in the classification of various fault types. The results demonstrate a fault diagnosis accuracy of 99.48%, affirming the effectiveness and superiority of the proposed method.

In order to explore the fatigue performance of the wind turbine foundation with embedded ring when the blade mass is imbalanced, the additional load is derived by reconstructing the blade mass imbalance model of the wind turbine, a singlepoint simulation of the pulsating wind velocity spectrum is done based on the harmonic synthesis method theory to calculate the basic operating load such as the aerodynamic load of the wind turbine, the finite element model of the wind turbine bladetowerfoundation integration is established with the actual engineering as an example, and the structural selfresonance characteristics and the load response under the combined action of the basic operating load and the additional load are calculated. The results show that the deepening of the imbalanced quality of the wind turbine blades will lead to the intensification of the stress concentration phenomenon and the increase of the stress amplitude of the basic structure, which in turn will affect the fatigue performance and fatigue life of the structure. and the force characteristics of the concrete in the structure will be greatly affected, followed by the steel cage, and the foundation embeddedring is the smallest.

In order to improve the control performance of wind turbine electrohydraulic pitch system, a fractional terminal sliding mode control method based on perturbation observer is proposed. The mathematical model of the wind turbine electrohydraulic pitch system is established, and the slidingmode state and perturbation observer is used to compensate the uncertainty and unknown disturbance of the pitch system parameters in real time. Fractional calculus theory is used to design the sliding mode surface of the terminal sliding mode controller, which can improve the jitter of the sliding mode control itself while ensuring the finite time convergence. Simulink is used for experimental verification, and the results show that the method enhances the antiinterference ability of the pitch system, weakens the jitter of the system, improves the tracking accuracy of the pitch angle, and improves the stability of the pitch system.

Based on the concept of load safety margin, the structure optimization inversion design was complemented for one offshore wind turbine supported by bucket foundation in order to reduce the amount of materials and structural cost while ensuring the strength and stability requirements of the structure. Hence, the optimization feedback analysis model and calculation process of offshore wind turbine supported by bucket foundation has been established and the origin bucket foundation was optimization design considering the three safety margin values of 1.10, 1.20 and 1.30. It can be seen in the results that the optimized foundation structure still has a better safety reserve after considering the safety margin with the design indicators of the bucket foundation structure, which all can meet the design requirements. This research provides a new idea for the optimization design of offshore wind turbine structure.

As the proportion of renewable energy and variable loads in the distribution system gradually increases, the uncertainty of power flow in the distribution network will affect the optimal network topology. Since distributed generation and demand response are affected by the time factor, the topology obtained by modeling at a single time period is difficult to be optimized at different times of the day. To address this uncertainty, this paper proposes a secondorder cone optimizationbased distribution network reconfiguration model for multitemporal tidal flow analysis for billing and demand response. By considering the "sourcestorageload" structure of the actual distribution system, an optimization problem with the objectives of network operation cost and switching operation cost is established, and the secondorder cone relaxation is used to transform the nonconvex search space into a convex feasible domain for fast solution. Experimental results on an improved IEEE 33 node distribution network show the superiority of the proposed method over traditional methods in terms of accuracy and solution speed.

Voltage violation has become an important factor limiting the maximum integration capacity of photovoltaics. To address the issue of voltage violation caused by largescale photovoltaic grid connection, the article proposes a grouped coordinated voltage control strategy for distribution networks with high proportions of photovoltaics. Firstly, based on the different voltage sensitivities of photovoltaic connection nodes in the distribution network, the concept of grouped coordinated control for photovoltaic inverters is introduced. Then, within each group of photovoltaic inverters, voltage control is carried out using capacity utilization ratio and power factor as consistent variables, while intergroup coordination control ensures that the voltage at key nodes converges to the set value of 1.05 p.u.. Finally, through case simulations, the proposed control strategy is verified to effectively suppress voltage violations in distribution networks, avoid unnecessary active power reduction, and demonstrate strong robustness during load and photovoltaic fluctuations.

The article addresses the problem of relatively low accuracy of traditional PV power prediction and proposes a hybrid TOPSISGRNN based mechanismdata driven PV plant power prediction model. Firstly, the correlation analysis of several meteorological indicators and the output power of PV power plant is carried out, and the meteorological data with high correlation is selected as the input factor of the model. The TOPSIS algorithm was used to select the optimal similar days, and then the theoretical values of their PV plant output power and meteorological data were used to build the GRNN prediction model. Finally, the model was simulated and validated by combining the historical meteorological data and power data on the DKASC website. The final test results yielded an average power prediction accuracy of 0.826 9 kW for RMSE, 3.45% for MAPE and 0.019 5 kW for MAE. The prediction accuracy of this forecasting method is significantly higher than that of a single forecasting model and has some theoretical and practical value.