Considering the influence of the tower shadow effect of wind turbines, and aiming at the problem that the elevation angle of wind turbines makes the aerodynamic characteristics of wind turbines more complicated, the flow field of horizontal axis wind turbines with different elevation angles was numerically simulated in this paper, and the pressure distribution of wind turbine blade cross section, vorticity and the change law of the tower cylinder surface pressure with phase angle were analyzed, so as to explore the influence of the elevation angle of wind turbines on the output power of wind turbines. The results show that increasing the rotor elevation angle can reduce the blade surface pressure, decrease the pressure difference at the tip part, and reduce the high vorticity area on the blade surface. Adding elevation angle to the wind turbine reduces the influence of the blade on the tower barrel, and the high vorticity area on the tower barrel surface gradually decreases with the increase of the wind turbine elevation angle, thus reducing the pressure fluctuation on the tower barrel surface. When the blade passes through the tower, the tower shadow effect has a great influence on the wind turbine, and the output power of the wind turbine decreases. When the blade is upright, the wind turbine output power reaches its maximum. After the elevation angle is added to the wind turbine, both the output power of the wind turbine and the elevation angle of the wind turbine wheel increase first and then decrease. The output power of wind turbine increases when the elevation angle of wind turbine is 3°, and the fluctuation decreases when the elevation angle is 6 °. The relevant conclusions can provide data support for the operation of wind turbine.

The INVELOX wind power generation system is a kind of wind collection system with ducts, which can obtain wind power in multiple directions and at low wind speeds. The system efficiency depends on the ratio of the wind speed of incoming wind direction to the average wind speed of the venturi, that is, the velocity ratio SR. In this paper, model optimization was carried out based on INVELOX system, and taking the design of a small style wind collection device as the research object. The fluid dynamics calculation software XFlow based on Lattice Boltzmann method (LBM) was used to numerically simulate the flow field characteristics of the device at different wind speeds. By calculating the SR ratio in the Venturi tube, the critical working wind speed was 3 m/s. Through the analysis of the VSR diagram, it can be concluded that the device enhanced the wind speed in the environment with the increase of the wind speed in the flow field. At the same time, considering the application in the environment, taking 6 m/s as the wind speed of the flow field and carrying out the simulated analysis of the horizontal and oblique incoming wind to obtain the wind speed variation in the working section of the Venturi tube at different Angle of attack, which provides a reference for the engineering application of the energy acquisition device.

In view of the insufficient research on the influence of wind shear on wake at present, two lidars were used to carry out wind field experiments in a wind farm, analyzed the phenomenon of wind shear under different wind speeds and the characteristics of wake change under different incoming flow conditions, and used a threedimensional wake model to verify the vertical wake profiles. The results show that the wind speed has an obvious effect on wind shear, and the wind shear effect increases with the increase of wind speed, and the wind shear index increases about 0.05 for every 1 m/s increase of the wind speed. The wind shear effect has a great influence on the distribution characteristics of the wake. The stronger the wind shear effect is, the greater the gradient of the wake velocity along the height direction, and the greater the width and length of the wake. The predicted curve of the model near the hub center line of the wind turbine and the measured wake data fit well, and the relative errors are basically within 10%, while the relative errors of the prediction near the ground side are large due to the influence of the terrain.

The boost capability of conventional Buck/Boost converter is weak and the power switches suffer from high voltage stress (equals the voltage at the highvoltage side (HVS)), reducing the conversion efficiency. Further, since the HVS current pulsates greatly, large capacity capacitors are required to meet the requirements of current ripple, decreasing the system reliability. Therefore, this paper proposes an improved Buck/Boost converter. By introducing one switch, one inductor and two capacitors into the conventional topology, the proposed converter has continuous input and output current, which greatly reduces the current stress of HVS filter capacitor. The voltage gain in Boost mode is increased to (2D₁)/(1D₁), and all switches have the same low voltage stress, which equals the difference between the voltages at lowvoltage side (LVS) and HVS, so it has higher conversion efficiency. The operation principle, steadystate characteristics, dynamic model and control strategy are analyzed in detail. Its feasibility is verified on a 100 W/120 kHz prototype. The experimental results demonstrate an enhanced efficiency performance over wide operating operations with a maximum efficiency of 95.6%.

With the proposal of the "double carbon" goal, the structure of the new power system with new energy as the main body has changed significantly, especially the access of large capacity offshore wind power units, which has brought harmonic and other power quality problems to the grid. In order to study the characteristics of low frequency harmonics generated by fan connection, firstly, a theoretical model of low frequency harmonic content in the gridconnected current of fan is established. Then, an offshore wind power simulation model is built on the simulation software ETAP to verify the output harmonic characteristics of the wind farm under different output conditions. Finally, based on the output harmonic characteristics of the wind farm, the variation coefficient synthetic weighting method is proposed to optimize the configuration of the active power filter (APF) in the wind farm to improve the control effect of the harmonic in the wind farm, and the effectiveness of the method is verified by simulation based on an actual example.

With the increasing proportion of wind turbines connected to grid, the security and stability problem caused by wind farm separated from power grid are becoming more and more serious. So it is particularly important to improve DFIG fault ride through capacity and reduce the occurrence of offgrid events. In view of the problems, existing DFIG fault ride through control schemes are introduces first. Considering that frequently switched of DC chopper circuit is easy to cause voltage waveform distortion and supercapacitor control scheme has high economic cost, the DFIG fault ride through control scheme based on smart chopper circuit is further proposed. The proposed method is upgraded based on DC chopper circuit. It connects the unloading resistance with the DC bus through DC/DC converter and introduces active powerDC voltage droop control link to adjust the circuit resistance power dynamically during fault period. Besides it sets two modes of high and low voltage crossing, which can be started automatically according to grid connected voltage. Finally, the smart chopper circuit control scheme is verified in Matlab/Simulink. The simulation results show that considering the DC bus voltage suppression effect, the regulation time for voltage recovery, the distortion degree of rotor current and the economic cost of schemes, fault ridethrough control of DFIG based on smart chopper circuit has the most advantages.

This paper presents an integrated energy system (IES) multiagent game cooperative optimal scheduling strategy considering carbon quota and integrated demand response. Firstly, based on Stackelberg game theory and considering the initiative of demand side and energy storage side, a multiagent game interaction framework of source – load – storage is established. Secondly, with IES operators as leaders and energy storage operators and users as followers, the decisionmaking model of each stakeholder is established. In order to guide users to use energy scientifically and reduce system carbon emissions, a dual incentive policy based on carbon quota and realtime price guidance is introduced into IES operator model, and energy selling price and internal unit output plan are formulated with the goal of maximum net profit. Finally, genetic algorithm combined with CPLEX twostage algorithm is used to solve the proposed multiagent game model. The simulation results show that the proposed dual incentive strategy and game model can effectively take into account the interests of all parties, reduce the carbon emissions of the system without harming the interests of all parties, and realize the multiagent lowcarbon collaborative operation of IES.

In order to achieve rapid and accurate assessment of transient voltage stability in the power system following the integration of wind farms into the grid, a transient stability assessment metric is proposed based on Convolutional Neural NetworksLong ShortTerm Memory (CNNLSTM) and attention mechanisms. To better capture spatial and temporal correlations in the input data, feature dimensionality reduction is carried out using Kernel Principal Component Analysis (KPCA). Addressing challenges related to decreased shortcircuit capacity and increased shortcircuit current levels in highproportion renewable energy grids, an active support measure is introduced by installing superconducting fault current limiters to restrict shortcircuit current levels during fault processes and maintain voltage stability at grid connection points. Finally, simulations and data collection are performed on an IEEE39 node system with wind power integration using PSDBPA. The results indicate that the KPCA approach effectively screens features of significant importance in the transient stability assessment of power systems. The proposed evaluation metric demonstrates higher discriminative capability, and the suggested improvement measures are observed to play a positive role in enhancing transient voltage stability in highproportion wind power integration systems.

With the marketoriented reform of power grid companies, the power market will gradually attract the investment of various social capital. The transformer districts (TDs) subordinated to the distribution network and the distribution network itself provided a platform for the multiagent competition, forming a competitive game pattern. At the same time, the high proportion of DRE access improves the cleanliness of the distribution network, but the uncertainty of DREs' output also leads to the further increase of the distribution network dispatching operation risk.To mitigate the uncertainty, the distributed renewable energy, distributed thermal power generation, energy storage and flexible load within the same TD is treated as a whole and regulated by the distribution grid operator with the objectives of safety and economy. Firstly, a leader follower game model consists of the distribution grid operator and multiple transformer districts is established to coordinate the interests between the distribution grid operator and its subordinate TDs. Conditional valueatrisk theory is used to quantify the uncertainty risk caused by renewable energy represented by wind and solar power. Next, the profit of each TD in the carbon market is incorporated into the optimization scheduling model to further consider the carbon emission costs of distributed thermal power generation achieving flexible complementary regulation between distributed renewable energy and thermal power. The BP neural network is used to fit the model, simplifying the leaderfollower game model into a singlelevel model, which is then solved using a particle swarm algorithm. Finally, the variations in distributed power generation within each TD under different renewable energy output risks and carbon prices are discussed to further validate the effectiveness of the model.

With the increasing penetration of distributed energy in the power system and its output uncertainty, the distribution system presents greater complexity and uncertainty, which will have an impact on the reliability of the power network. In order to determine the optimal installation location and capacity size of renewable units in the distribution network system, this paper proposes a reliability assessment framework by combining the stochastic fuzzy expected value operator and Markov Monte Carlo method. The model first establishes the multi state probability density functions of wind and PV outputs, and subsequently employs the stochastic fuzzy expected value operator to simulate the uncertainties of power loss and voltage stability in the distribution network. The stochastic nature of all nonsource components in the distribution system is modeled using the Markov Monte Carlo method to generate distribution network component failure events and recovery times from an exponential distribution, considering the topology of the distribution system. Three reliability indices, namely, average system outage number, average system outage duration, and power shortage expectation, are evaluated on the IEEE 33 node standard distribution network, and the experimental results demonstrate the effectiveness of the proposed method.