Wind turbine blades are subjected to various loads during operation, which can cause deformation, and yaw can make the force situation of the blades more complex. To investigate the dynamic flapping deformation of blades under yaw conditions, experimental research was conducted using digital image correlation (DIC) technology to explore the influence of changes in yaw angle, wind speed, and speed on the dynamic flapping deformation of blades. The results show that the dynamic flapping deformation of horizontal axis wind turbine blades varies in a sinusoidal pattern, and the higher the wind speed, the greater the dynamic flapping deformation. The higher the rotational speed, the greater the dynamic flapping deformation, and at the same time, the time it takes to reach the maximum value is also shorter, with more variation cycles experienced; The existence of yaw angle changes the force situation of the blade. The larger the yaw angle, the greater the trend of dynamic flapping deformation. The shorter the time it takes to reach the peak, the earlier the peak position is. At the same time, the proportion of positive dynamic flapping deformation decreases, and the proportion of negative dynamic flapping deformation increases. The most obvious trend is at a 30° yaw angle. The research results of this article can provide experimental data support for effective control of blade deformation and subsequent research on the impact of blade deformation on the aerodynamic characteristics of wind turbines.

China's shallowsea development potential is 1 730 GW, and deepsea development potential is 1 830 GW, making China the country with the largest offshore wind power development potential in Asia. In recent years, with the continuous breakthroughs in floating wind turbines and concerning technologies, offshore wind power is gradually moving towards the deep sea. The development and delivery costs will drop rapidly. According to calculations, by 2030, the LCOE of floating wind power will drop to 0.28 ¥/(kW·h), and by 2050 it will drop to 0.14 ¥/(kW·h). The use of VSCHVDC for deepsea floating wind power, by 2050, the transmission costs of offshore 100 km, 150 km, and 200 km are estimated to be 0.050, 0.059 ¥/(kW·h)and 0.068 ¥/(kW·h) respectively in the basic scenario. Under the scenario of rapid technological progress, the estimated results are 0.033,0.040 ¥/(kW·h) and 0.046 ¥/(kW·h) respectively.

The rapid simulation of wake flow has important scientific significance and engineering application. In this paper, a fast calculation method is constructed based on the equation of vortex, and a plane wake is simulated and investigated based on this method. The reliability of this method is validated through comparison with results from previous studies. It is found that this fast calculation method can accurately simulate the formation and evolution of Karman vortex street in the wake region. Analysis of the wake profiles reveals that the positions at which different turbulence statistics reach a selfsimilar state vary, and a nonequilibrium selfsimilar region is observed upstream of the wake. The results of the present study not only enhance our understanding of turbulent wake characteristics, but also be of significance for engineering applications, such as predicting and controlling wind turbine wakes in wind farms.

With the development of photovoltaic(PV) industry, high capacity ratios have gradually become popular in the PV power station. To find the optimal charging/discharge strategy of energy storage (ES) in PV subarray with a high capacity ratio, one operation strategy based on working mode recognition was proposed to coordinate two competitive objectives—load shifting and smoothing. Furthermore, a capacity configuration model with the objectives of life cycle net present value maximization and output fluctuation minimization was constructed considering the generation income, ES cost, fluctuation characteristics, and typical day type. Moreover, taking a 1 MW subarray with 1.8 capacity ratio in a northeast utilityscale PV power station as a case, the optimal capacity of 700 kW·h was obtained. The simulation results under different typical days verified the feasibility and the effectiveness of the proposed ES operation strategy as well as the configuration model.

As a clean and lowcarbon energy system, the integration of wind, solar, and hydrogen microgrids plays an essential role in facilitating the transformation of energy structures and enhancing energy utilization efficiency. This paper investigates the capacity configuration issues of wind, photovoltaic, and hydrogen storage microgrid systems. A model of the windsolarhydrogen microgrid system has been developed, taking into account the uncertainties in wind and solar outputs. Based on historical data, typical daily scenarios are selected using an improved Kmeans clustering algorithm, and the uncertainty probability distributions are jointly constrained by both the 1norm and infinity norm within a confidence set. This study proposes a twostage distributionally robust model for the capacity configuration of windsolarhydrogen microgrids. The first stage determines the capacity of each component with the goal of minimizing investment costs, while the second stage aims to minimize operational costs. The solution to the model is derived through the application of the ColumnandConstraint Generation (C&CG) algorithm. The results indicate that the model can achieve a rational configuration of capacity, and it enhances the energy utilization efficiency and economic performance of the windsolarhydrogen microgrid.

In response to the difficulties faced by the power system in wind power consumption and the shortage of regulation capacity, this article establishes a robust optimization scheduling model for source load distribution that takes into account green certificate carbon trading. Firstly, green certificate trading mechanism and carbon trading mechanism are introduced on the power supply side to enhance the grid connected power of wind power, and high load capacity is introduced on the load side to improve the system regulation capability; Secondly, in order to reduce the impact of uncertain wind power output, a datadriven distributed robust method is adopted to construct a probability distribution uncertainty set based on historical wind power output data, and then optimize the worstcase scenario using column constraint generation algorithm; Finally, based on the IEEE 39 node system, the verification results show that by integrating adjustable resources from both the source and load sides for collaborative optimization, it is possible to promote wind power consumption while ensuring good regulation capability of the power system.

Given the increasing proportion of new energy power generation, the deepening of electricthermal coupling, and the high carbon emissions of coalfired units, a multitimescale scheduling model of multienergy system including carbon capture power plants is established based on new energy optimal consumption and electricthermal demand response. First, the carbon capture coalfired power plant model with integrated flexible operation mode is established. It can reduce the carbon emissions of the system and improve the flexibility of coalfired units to cooperate with new energy sources. Second, the different demand response resources are applied to the load demand of different time scales, which can reduce the load peaktovalley difference and cooperate with the optimal consumption strategy of new energy to explore the lowcarbon characteristics of carbon capture based coalfired power plants. Third, considering multiple types of power and heat source equipment and taking the minimization of system operating costs as the objective function, a dayahead intraday realtime multi time scale scheduling model is established for sourceload coordination. It can optimize the load distribution and unit output plan under different time scales, and improve the new energy consumption capacity. Finally, the effectiveness and feasibility of the model are verified by experimental simulation results.

In the context of new power systems, represented by renewable energy sources such as wind and solar, low system inertia and high uncertainty have led to prominent issues with grid frequency stability. While new energy sources with virtual inertia control have improved frequency stability to some extent in lowinertia grids, they have simultaneously increased the difficulty of inertia assessment in the grid. Addressing the challenge where traditional online inertia monitoring methods struggle to accurately estimate synchronous machine rotational inertia alongside virtual inertia from new energy sources, this paper proposes a comprehensive estimation method for rotational and virtual inertia in power systems based on multiimportance sampling and Bayesian inference without requiring any linear assumptions. This approach utilizes local measurements from PMUs (Phasor Measurement Units) within a Bayesian inference framework and employs multiimportance sampling algorithms to sample from the nonGaussian posterior distribution of inertia parameters, ensuring the accuracy of inertia estimation. Simulation results demonstrate that this method exhibits high precision in online inertia estimation for both synchronous and asynchronous generators and can be widely applied in novel electric power systems dominated by new energy sources.

Lowcarbon development of the power industry is an important measure for the dualcarbon goal. In order to promote carbon emission reduction and improve the economy, reliability and environmental protection of the multienergy system, an optimization model for the carbon emission reduction of the multienergy system considering the coordination of economy and reliability is proposed in this paper. Firstly, the coordination model of LowCarbon MultiEnergy System (LCMES) is established by analyzing the topology of the LCMES including electricity, gas and heat; Secondly, based on the fault characteristics of the energy conversion and storage equipment in the LCMES, the multistate reliability model of the LCMES is established; Then, under the conditions of operation constraints and reliability constraints, an optimization model of carbon emission reduction of the LCMES considering the coordination of economy and reliability is proposed with the objective of minimizing the operation cost and carbon emissions of multienergy system; Finally, it is verified by simulation numerical example that the multienergy system optimization model proposed in this paper can ensure the improvement of the operation reliability and economy of the multienergy system while achieving the carbon emission reduction.

To improve the fragmentation rate , particle size uniformity, and stability of straw micropulverization, a composite pulverizing method of moving and fixed cutter impact shear was proposed for the physical properties of straw, and a curved serrated blade pulverizing cutter was designed. The main factors affecting the pulverizing performance of straw and the way of fragmentation were clarified through the analysis of the shear mechanics of straw, the analysis of impact dynamics, and the mechanical analysis of pulverizing moving cutter. Based on EDEM numerical simulation, the effects of the serrated blade and smooth blade cutters on the pulverizing performance of straw were compared and analyzed. The simulation results show that when pulverizing corn straw with a moisture content of 20%, the number of connective keys of the serrated blade is 16.76% less than that of the smooth blade, the particle motion speed is increased by 15.9%, the total energy of particles is increased by 25.05%, and the impact force on the pulverizing chamber wall is reduced by 33.69% , and has a smoother working condition and lower energy consumption.