Large-scale Permanent Magnet Research Articles

Analysis of electromagnetic characteristics of typical faults in permanent magnet wind generators

Due to the harsh actual operating environment of the permanent magnet wind turbine, it is easy to break down and difficult to monitor. Therefore, the electromagnetic characteristics identification of major fault types of large-scale permanent magnet wind turbines is studied in this paper. The typical faults of rotor eccentricity, stator winding short circuit and permanent magnet demagnetization of permanent magnet wind turbines are analyzed theoretically. The wavelet analysis algorithm is used to decompose and reconstruct the abnormal electromagnetic signal waveform band, and the characteristic frequency of the electromagnetic signal is obtained when the fault occurs. In order to verify the effectiveness of the proposed method, a 3.680MW permanent magnet wind turbine was taken as the research object. Its physical simulation model was established, and an external circuit was built to carry out field co-simulation. The results show that the motor fault type can be determined by detecting the change rule of fault characteristic frequency in the spectrum diagram, and the electromagnetic characteristic analysis can be applied to the early monitoring of the permanent magnet wind turbine fault.

New magnetic isolation winding for modular multiple three‐phase permanent‐magnet machine with mixed‐layer

In large scale permanent magnet (PM) machines, such as direct drive wind power generators, stator modularity is widely used for easy manufacturing and to protect the winding from mechanical damage due to being exposed to air. Multiple three-phase systems that use commercial inverters provide not only a fault-tolerant operation but also price competitiveness. Although the conventional modular structure of a concentrated single-layer or distributed winding shows good performance, a large magnetic mutual interference between coils is inevitable. Consequently, if conventional windings are applied to multiple three-phase systems, complexity and difficulty for controlling the machine can arise. This study proposes a new magnetic isolation winding scheme for modular multiple three-phase PM machines with a mixed layer to deal with the abovementioned limitation. For comparison, five different modular multiple-three phase PM machines with a mixed-layer winding (MMPM) are presented and three conventional modular types are selected. Then, several simulation results and experimental data confirm the validity of the proposed structure.

Design and Optimization of a Large-Scale Permanent Magnet Synchronous Generator

Direct drive permanent magnet synchronous generators have numerous advantages such as improved reliability, low maintenance, long life, and developed performance characteristics. Focus of this paper is on the development of a step-by-step method for the design of a permanent magnet synchronous generator. Then the winding function method is used to model the generator and to analytically calculate its output characteristics. The analytical results of the designed generator are evaluated with the finite element analysis (FEA) results and it is demonstrated that the achieved results from both methods are well matched with the experimental measurements of the Northern Power direct-drive generator. The sensitivity analysis and the optimization based on the genetic algorithm are used to achieve an optimum generator. The optimization goal is obtaining higher efficiency and power factor with lower required permanent magnet (PM) volume and voltage regulation for the optimum machine compared to the initial design. In addition, the calculation of the voltage total harmonic distortion (THD) is presented and the optimum skew angle for the optimum generator is computed to reduce the voltage THD.

Demagnetization Performance of a 7 MW Interior Permanent Magnet Wind Generator With Fractional-Slot Concentrated Windings

High reliability is one of the most important requirements for large-scale permanent magnet (PM) wind generators. However, the magnet suffers partially irreversible demagnetization due to the material property, especially under short-circuit conditions. To improve fault-tolerance capability and torque density, fractional-slot concentrated windings (FSCWs) have been adopted in wind generators. However, the rich harmonics of magnetomotive forces make the demagnetization characteristics different from that of generators with distributed windings. In this paper, the partial demagnetization performance of a 7 MW interior PM wind generator with FSCWs is investigated, under the symmetric short-circuit condition. In addition, influences of slot–pole combinations and rotor types are analyzed to improve the antidemagnetization capability. The transient magnetic behavior is evaluated by the finite-element analysis.

Influence of Wind Farm with PMSG Type on Small Signal Stability of Power System

In order to study the small signal stability of power grid after grid-connection of large-scale Permanent Magnet Synchronous Generator (PMSG) wind farms, the mathematical model of PMSG was established. By means of simulation on a simple power system, the damping characteristics of grid under different wind power penetration and different access location of wind farms were studied in detail. Simulation results show that along with the increase of wind power, the inter-area oscillation mode damping would reduce. When wind farm was attached the receiving area, the inter-area oscillation mode damping was lower than it when wind farm was attached the supplying area.

Diagnosis of Short-Circuit Fault in Large-Scale Permanent-Magnet Wind Power Generator Based on CMAC

This study proposes a method based on the cerebellar model arithmetic controller (CMAC) for fault diagnosis of large-scale permanent-magnet wind power generators and compares the results with Error Back Propagation (EBP). The diagnosis is based on the short-circuit faults in permanent-magnet wind power generators, magnetic field change, and temperature change. Since CMAC is characterized by inductive ability, associative ability, quick response, and similar input signals exciting similar memories, it has an excellent effect as an intelligent fault diagnosis implement. The experimental results suggest that faults can be diagnosed effectively after only training CMAC 10 times. In comparison to training 151 times for EBP, CMAC is better than EBP in terms of training speed.

An Application of Latin Hypercube Sampling Strategy for Cogging Torque Reduction of Large-Scale Permanent Magnet Motor

An adaptive response surface method with Latin hypercube sampling strategy is employed to optimize a magnet pole shape of large-scale brushless direct current (BLDC) motor to minimize the cogging torque. The proposed algorithm consists of the multi-objective Pareto optimization and (1+ lambda) evolution strategy to find the global optimal points with relatively fewer sampling data. In the adaptive response surface method (RSM), an adaptive sampling point insertion method is developed utilizing the design sensitivities computed by using finite-element method to get a reasonable response surface with a relatively small number of sampling points. The developed algorithm is applied to the shape optimization of PM poles for 6 MW BLDC motor, and the cogging torque is reduced to 19% of the initial one.