In order to make reliable dynamic prediction of the potential risk of pitch system, aiming at the problems of multiple components, complex system and difficult fault feature extraction of pitch system, the fault tree is established through the induction and analysis of its fault point and fault transmission process, and then it is transformed into a dynamic Bayesian network (DBN) integrating Leaky Noisyor nodes, which ensures the accuracy of the model and has the dynamic prediction ability. The model is optimized and verified by using a 5fold crossvalidation method. The test results show that this method has high accuracy in risk prediction, fault cause analysis and risk dynamic evolution process analysis of pitch system, and has engineering application value in guiding the preventive maintenance of pitch system and ensuring the overall safety of wind turbine.

Citric acid is one of the most productive biomass organic acids in the world and has been widely used. In this paper, we used reduced iron powder as iron source, citric acid as multidentate ligand and carbon source, and used ammonia to enhance the coordination solubilization ability of citric acid to iron powder, so that it could quickly form a homogeneous complex solgel, which was then carbonized to obtain carboncoated coreshell ironbased FischerTropsch catalyst. In the performance test, the catalyst synthesized by direct dissolution of iron powder with citric acid exhibited remarkable catalytic activity and stability, giving the CO conversion of 99.2%, C5+ hydrocarbon selectivity of 53%, and the CO conversion activity was stably kept above 97.3% for a time on stream of 168 h. The citric acid coordination method is greener and safer, which avoid the use of iron salts such as ferric nitrate, and the risk of explosion and toxic gases in the reduction process of iron salts. This synthesis method provides a new idea for the green and safe production of catalysts.

In order to accurately predict the thermal and electrical performance of solar photovoltaic/thermal (PV/T) systems, this study utilized the Particle Swarm Optimization (PSO) algorithm to optimize the Radial Basis Function (RBF) neural network. Based on this method, a simulation prediction model for the performance of solar PV/T systems was established and compared with a prediction model based on an unoptimized RBF neural network. Additionally, this research built a solar PV/T experimental platform and collected experimental data using a cloud platform for the aforementioned model. The research results indicate that the RBF neural network model optimized using the PSO algorithm exhibits better prediction accuracy compared to the unoptimized RBF neural network model. The optimized RBF neural network model demonstrates a 20% improvement in prediction accuracy and a 30% increase in prediction stability compared to the unoptimized model. The goodness of fit, as indicated by the Rvalue, is also improved compared to the unoptimized model. The prediction model established based on the PSORBF neural network can accurately predict the thermal and electrical performance of solar PV/T systems.

In order to reduce the influences of renewable energy power fluctuations on power systems, an energy storage configuration optimization method considering renewable energy power probability distribution is proposed in this paper. Firstly, calculate and count the renewable energy power fluctuations at different time scales, and determine the probability distribution characteristics of renewable energy power. Secondly, according to the probability distribution characteristics and the gridconnected index of renewable energy, the configuration optimization model of energy storage considering the renewable energy timescale and power fluctuation is set up. Thirdly, based on the given constraints and time scale, calculate the minimum energy storage charging and discharging power where the fluctuations meet any set probability levels, thereby determining the rated power, capacity and initial state of the energy storage. At last, through calculation and analysis using the data measured from a 50 MW photovoltaic power station, the method is proved to be correct and effective. This method only compensates the fluctuated power that does not meet the fluctuation index, and has no impact on the power that has already satisfied.

The wind turbines are subjected to continuous wind loads during their whole service life and are inevitably resisted earthquake action. In this paper, a large megawatt wind turbine is taken as the research object to simulate and analyze its deformation and mechanical responses under the conditions of normal operation, earthquake during shutdown and earthquake during operation. The results show that the deformation of wind turbine increases with the increase of tower height, and the horizontal displacement of the wind turbine under the earthquake is obviously less than that under the wind turbine operation state. With the increase of earthquake level, the horizontal displacement of the wind turbine is gradually increased. The deformation shape of the wind turbine remains unchanged, and the deformation of tower top is large. The influence of the wind turbine operating load on structural deformation response is significantly greater than that of small and medium earthquake actions. Meanwhile, the deformation response of the wind turbine under the combined action of operating load and earthquake is significantly greater than that under the separate action of two loads. In the structural design of the wind turbine, it is necessary to consider the coupling effect of the operating state and the earthquake. The stress response at the top of the tower is the largest, and its crosssection should be checked in the design.

In this paper, a reactive power optimization method for wind farms considering the reactive power resources allocation cost is proposed to achieve the optimal reactive power control under different operating conditions. With the comprehensive cost composed of power loss and reactive power cost as the objective function, the reactive power optimization model is established based on chanceconstrained programming, considering the influence of wind power fluctuations on voltage magnitude, which is then solved by the improved interior point method. According to the actual operating requirements, the proposed method can schedule reactive power of Static Var Generator (SVG), Energy Storage (ES) and wind generators in sequence by setting reactive power cost coefficients, and optimize the power loss of wind farm. The voltage violation risk is also controlled by reserving the voltage safety margin in the voltage constraint. In the end, the advanced and feasibility of the proposed method is verified by a simulation at an actual wind farm in China.

With the high penetration of renewable energy and electronic equipment, the problem of wideband oscillation in power systems is becoming increasingly prominent, which has become a key factor restricting the efficient consumption of renewable energy. A wideband phasor measurement method is proposed and the corresponding device is developed to satisfy the requirements of wideband oscillation mitigation and protection in power systems with renewable energy. Based on the windowed discrete Fourier transform and three peak interpolation, this device can measure multi –mode wideband phasor of multiple voltages and currents. Besides, the amplitude and phase of high frequency phasor are compensated based on the linear regression, which effectively improves the measurement accuracy of the device while ensuring the dynamic response speed. Finally, the measurement performance of the developed device was verified by experimental testing with testers and realtime digital simulation, and the device can provide support for ensuring the safety and stability of power systems and the consumption of renewable energy.

Density functional theory calculations were employed to investigate the mechanisms and energy changes involved in C–C bond cracking, CH₄ reforming, and water gas shift reactions in the tar reforming process. The findings reveal that, in the CC bond cracking reaction, C₃H₈ initially adsorbs onto the catalyst surface to form adsorbed C₃H₈*, subsequently undergoing cleavage to produce CH₃* and CH₂CH₃*. While the cracking reaction is exothermic, it is hindered by a significant energy barrier and difficult to carry out. In the CH₄ reforming reaction, CH₄* undergoes sequential dehydrogenation reactions, producing CH₃*, CH₂*, and CH*. Comparatively, CH* has a greater tendency to react with OH* to form CHO*, which further undergoes dehydrogenation to form CO*. Additionally, H* generated in each step combines to form H₂*. Throughout the CH₄ reforming process, the ratelimiting step is the cracking of CH₂* to CH*. In the water gas shift reaction, the OH* species formed from H2O* decomposition prefers to combine with CO* to generate COOH* rather than directly reacting with H* to produce H₂*. COOH* removes H and generates COO*, which is the rate limiting step.

Ammonia synthesis based on hydrogen derived from renewable electricity (i.e. green hydrogen and green ammonia process) is frequently fluctuated due to weather change and the sections are highly coupled. To understand the synthesis and scheduling of power generation and transmission, hydrogen production by water electrolysis, hydrogen storage, electrochemical energy storage, and ammonia synthesis sections in green ammonia process, a generic process model for both steadystate and dynamics mode was developed using the next generation process simulation software, AVEVA Process Simulation, and the dynamics response of the model to weather fluctuation was investigated by means of multisteady state simulation. The results show that optimized design and scheduling of the hydrogen storage and electricity storage modules can significantly stabilize the ammonia production, utilize excess renewable electricity, reduce grid power input, and thus, improve the economy.

The amount of solar radiation and wind load will directly affect the continuous generation of solar thermal power station. Therefore, according to the actual environmental conditions of Zhongdian Nao Maohu solar thermal Power Station in Hami region, Xinjiang, a threedimensional numerical model of heliostat group was established to simulate the heating conditions and flow field characteristics of the mirror group under solar radiation and upwind Angle in different seasons, and the distribution of mirror flares and pulsating wind pressure coefficients under different wind incidence angles were analyzed. The results show that the simulated drag coefficient and lift coefficient are in good agreement with the related research results, which verifies the validity of the model. The distribution of flares in different seasons is similar and mainly depends on the variation of solar direction Angle. With the increase of the wind incidence Angle, the wake region of the mirror cluster decreases first and then increases. Since the wake in the helioscope group can effectively inhibit wind pressure, the internal stability can be ensured by combining the arrangement of the group. Among them, the center of the regular pentagonal helioscope maintains a low pulsating wind pressure, which greatly improves the force balance of the mirror.