The time and space characteristics of magnetomotive force in the cascaded linear induction motor

To choose a reasonable mode of three-phase winding for the improvement of the operating efficiency of cascaded linear induction motor, the time and space characteristics of magnetomotive force were investigated. The ideal model of the cascaded linear induction motor was built, in which the B and C-phase windings are respectively separated from the A-phase winding by a distance of d and e slots pitch and not overlapped. By changing the values of d and e from 1 to 5, we can obtain 20 different modes of three-phase winding with the different combinations of d and e. Then, the air-gap magnetomotive forces of A-, B-, and C-phase windings were calculated by the magnetomotive force theory. According to the transient superposition of magnetomotive forces of A-, B-, and C-phase windings, the theoretical and simulated synthetic fundamental magnetomotive forces under 20 different arrangement modes were obtained. The results show that the synthetic magnetomotive force with d = 2 and e = 4 is close to forward sinusoidal traveling wave and the synthetic magnetomotive force with d = 4 and e = 2 is close to backward sinusoidal traveling wave, and their amplitudes and wave velocities are approximately constant and equal. In both cases, the motor could work normally with ahigh efficiency, but under other 18 arrangement modes （d= 1, e=2; d= 1, e=3; d= 1, e=4;...）, the synthetic magnetomotive force presents obvious pulse vibration and moves with variable velocity, which means that the motor did not work normally and had high energy loss.

Model of DFIG Wind Farm and Study on Its LVRT Capability

As a typical clean and renewable energy, wind power is becoming more and more widely used in electrical industry. However, its characteristics of random and intermittent have brought serious problems to the power system, such as voltage fluctuation and insufficient reactive power. Based on the K-means clustering algorithm, this paper classifies the doubly-fed induction generators （DFIG） according to the operation of propeller pitch angle control. At the same time, to obtain the optimal parameter, advanced particle swarm optimization （PSO） is used. Then the dynamic model of DFIG under the network fault condition is built. What is more, the role that crowbar circuit plays in low voltage ride through （LVRT） is discussed. Finally, simulations in DigSILENT verify the model.

Adaptive Frequency Responsive Control for Wind Farm Considering Wake Interaction

With the increasing share of wind power,it is expected that wind turbines would provide frequency regulation ancillary service.However,the complex wake effect intensifies the difficulty in controlling wind turbines and evaluating the frequency regulation potential from the wind farm.We propose a novel frequency control scheme for doubly-fed induction generator(DFIG)-based wind turbines,in which the wake effect is considered.The proposed control scheme is developed by incorporating the virtual inertia control and primary frequency control in a holistic way.To facilitate frequency regulation in timevarying operation status,the control gains are adaptively adjusted according to wind turbine operation status in the proposed controller.Besides,different kinds of power reserve control approaches are explicitly investigated.Finally,extensive case studies are conducted and simulation results verify that the frequency behavior is significantly improved via the proposed control scheme.

Multiple Random Forests Based Intelligent Location of Single-phase Grounding Fault in Power Lines of DFIG-based Wind Farm

To address the problems of wind power abandonment and the stoppage of electricity transmission caused by a short circuit in a power line of a doubly-fed induction generator(DFIG) based wind farm, this paper proposes an intelligent location method for a single-phase grounding fault based on a multiple random forests(multi-RF) algorithm. First, the simulation model is built, and the fundamental amplitudes of the zerosequence currents are extracted by a fast Fourier transform(FFT) to construct the feature set. Then, the random forest classification algorithm is applied to establish the fault section locator. The model is resampled on the basis of the bootstrap method to generate multiple sample subsets, which are used to establish multiple classification and regression tree(CART) classifiers. The CART classifiers use the mean decrease in the node impurity as the feature importance,which is used to mine the relationship between features and fault sections. Subsequently, a fault section is identified by voting on the test results for each classifier. Finally, a multi-RF regression fault locator is built to output the predicted fault distance. Experimental results with PSCAD/EMTDC software show that the proposed method can overcome the shortcomings of a single RF and has the advantage of locating a short hybrid overhead/cable line with multiple branches. Compared with support vector machines(SVMs)and previously reported methods, the proposed method can meet the location accuracy and efficiency requirements of a DFIG-based wind farm better.

A complete modeling and simulation of DFIG based wind turbine system using fuzzy logic control

The current paper talks about the variable speed wind turbine generation system （WTGS）. So, the WTGS is equipped with a doubly-fed induction generator （DFIG） and two bidirectional converters in the rotor open circuit. A vector control （VC） of the rotor side converter （RSC） offers independent regulation of the stator active and reactive power and the optimal rotational speed tracking in the power maximization operating mode. A VC scheme for the grid-side converter （GSC） allows an independent regulation of the active and reactive power to exchange with the grid and sinusoidal supply currents and keeps the DC-link voltage constant. A fuzzy inference system （FIS） is adopted as an alternative of the conven- tional proportional and integral （PI） controller to reject some uncertainties or disturbance. The performances have been verified using the Matlab/Simulink soft-ware.