Fault Ride-Through Capability of Full-Power Converter Wind Turbine

In order to ensure power system stability, modern wind turbines are required to be able to endure deep voltage dips. The specifications that determine the voltage dip versus time are called fault r/de-through （FRT） requirements. The purpose of this paper is not only to examine the FRT behavior of a full-power converter wind turbine but also to combine the power system viewpoint to the studies. It is not enough for the turbine to be FRT capable; the loss of mains （LOM） protection of the turbine must also be set to allow the FRT. Enabling FRT, however, means that the LOM protection settings must be loosen, which may sometimes pose a safety hazard. This article introduces unique real-time simulation environment and proposes an FRT method for a wind turbine that also takes the operation of LOM protection relay into account. Simulations are carried out using the simulation environment and results show that wind turbine is able to ride-through a symmetrical power system fault.

Analysis of Transforming dq Impedances of Different Converters to A Common Reference Frame in Complex Converter Networks

DQ impedance-based method has been widely used to study the stability of three-phase converter systems.As the dq impedance model of each converter depends on its local dq reference frame,the dq impedance modeling of complex converter networks gets complicated.Because the reference frames of different converters might not fully align,depending on the structure.Thus,in order to find an accurate impedance model of a complex network for stability analysis,converting the impedances of different converters into a common reference frame is required.This paper presents a comprehensive investigation on the transformation of dq impedances to a common reference frame in complex converter networks.Four different methods are introduced and analyzed in a systematic way.Moreover,a rigorous comparison among these approaches is carried out,where the method with the simplest transformation procedure is finally suggested for the modeling of complex converter networks.The performed analysis is verified by injecting two independent small-signal perturbations into the d and the q axis,and doing a point-by-point impedance measurement.

High Linear Voltage Gain in QZNC Through Synchronizing Switching Circuits

The solar powered systems require high step-up converter for efficient energy transfer.For this,quasi-impedance network converter has been introduced.The quasi-impedance network converter(QZNC)is of two types:type-1 and type-2 configuration.Both the type-1 and type-2 QZNC configurations have drooping voltage gain profile due to presence of high switching noise.To overcome this,a new quasi-impedance network converter synchronizing the switching circuit with low frequency noise has been proposed.In this paper,the proposed QZNC con-figuration utilizes the current controlling diode to prevent the output voltage drop.Thus,the suggested topology provides linear high voltage gain profile,low load voltage ripple,and reduced impedance network stress and device stress.There-fore,the efficiency of proposed QZNC has been improved.The topology descrip-tion,working principle,parameter design and comparison with traditional converters are illustrated.Andfinally,both simulation and practical results are presented to confirm the converter characteristics and performance.From the results,it has been found that the performance of the suggested topology is better as it achieves a higher efficiency of 81%and hence,it is suitable for high power applications.

A Correlative Study of Perturb and Observe Technique and GA-RBF-NN Method Supplying a Brushless DC Motor

A comparative study is done in regards to the performance of the popular Perturb and Observe algorithm and the Genetic Assisted-Radial Basis Function-Neural Network (GA-RBF-NN) algorithm, both incorporating the Interleaved Boost converter. The Perturb and Observe method (P&O) is inarguably the most commonly used algorithm as its advantages pertaining to its ease in implementation and simplicity enable to track the Maximum Power Point (MPP). However, it is absolutely unreliable when subjected to rapidly fluctuating irradiation and temperature levels. More importantly, the system has the tendency to swing back and forth about the Maximum Power Point without reaching stability. At this juncture, the implementation of the Genetic-Assisted Radial Basis Function (GA-RBF) algorithm helps the system achieve MPP at a shorter time when compared to the Perturb and Observe technique. The ever reliable and robust Levenberg-Marquardt algorithm is included along with the MPPT controller that minimizes the Mean Square Error (MSE) and aids in faster training of the neural network. This PV system drives a brushless DC motor (BLDC), employing rotor position sensors.