Reliability Model Development for Wind Turbine Drivetrain with Brushless Doubly-Fed Induction Machine as Generator

Brushless doubly-fed induction machines (BDFIM) are attractive generators to be used in wind turbines due to the absence of brushes and slip rings. Furthermore, the BDFIM is a medium-speed generator and hence only requires one or two-stage gearbox. This feature simplifies the gearbox system and therefore improve reliability and reduce maintenance costs for the wind turbine. Although the design and operation of the BDFIM has been widely studied in the literature, there are only few studies on reliability assessment of the machine as a wind turbine generator. This paper proposes a comprehensive reliability model for two wind turbine drivetrain configurations: One with doubly-fed induction generator, and the other when the BDFIM is employed as the generator. The model is capable of evaluating the failure rate and repair rate indexes for the both configurations. Real field survey data from a 90 MW wind farm as well as calculated reliability data are then utilised to determine the reliability index values for the two drivetrain configurations in order to compare their reliability performance

A New Fault Diagnosis Approach for Brushless Doubly Fed Machines for Wind Turbine Generator Applications

The Brushless Doubly Fed Machine (BDFM) with high reliability and robust structure demonstrates commercial and technical advantages both as a generator and motor for variable speed applications. As a generator it is particularly attractive to be used in offshore wind turbines where reliability improvement and maintenance cost reduction are the key factors in market growth. As a motor it may be utilized for adjustable speed drives. In this study, a continuous wavelet transform (CWT) technique using a wavelet-based adoptive filter has been proposed for the BDFM fault detection as a generator operating in a wind turbine. Three different generator-typed faults namely rotor torque perturbation, rotor broken bar and grid overvoltage faults have been considered to assess the practicality of the proposed technique. The study has been performed on a D400 250kW BDFM

Eccentricity fault detection in brushless doubly fed induction machines

Abstract: A new fault diagnosis method for detecting the rotor eccentricity faults including static, dynamic and mixed eccentricity is proposed for brushless doubly‐fed induction machines (BDFIMs). BDFIMs are attractive alternatives for the conventional doubly‐fed induction generator (DFIG) for offshore wind power generation; therefore, paying attention to their fault detection is essential. Existing fault detection methods for conventional induction machines cannot be directly applied to the BDFIM due to its special rotor structure and stator winding configurations as well as complex magnetic field patterns. This article proposes a novel fault detection method based on motor current signal analysis to determine stator current harmonics, induced by the nested‐loop rotor slot harmonics (NRSHs), as fault indices. The analysis is performed under healthy conditions and with different types of rotor eccentricity. Finally, a sensitivity analysis is carried out to confirm the practicability of the proposed technique with various fault intensities and load conditions. Analytical winding function approach, finite element analysis and experimental tests on a prototype D180 BDFIM are used in this study to validate the proposed fault detection technique

Improved vector control methods for brushless double fed induction generator during inductive load and fault conditions

A Brushless Double-Fed Induction Generator (BDFIG) has shown tremendous success in wind turbines due to its robust brushless design, less maintenance, smooth operation, and variable speed characteristics. These generators are composed of two back-to-back voltage source converters, a Grid Side Converter (GSC) and a Rotor Side Converter (RSC). Existing control techniques use a “trial and error” method that results in a poor dynamic response in machine parameters during the absence of load. The RSC control is used for reactive current control during the inductive load insertion. However, it is more suitable for stabilizing steady-state behaviour, but it suffers from slow response and introduces a double fundamental frequency component to the Point of Common Coupling (PCC) voltage. In addition, generally, a Low Voltage Ride Through (LVRT) fault is detected using a hysteresis comparison of the power winding voltage. The LVRT capability is provided by using fixed reference values to control the winding current. This approach results in an erroneous response, sub-optimal control of voltage drops at PCC, and false alarms during transient conditions. This thesis aims to solve the mentioned issues by using an improved vector control method. Internal Model Control (IMC) based Proportional-Integral (PI) gains calculation is used for GSC and RSC. These are controlled to enhance the transient response and power quality during no-load, inductive load, and fault conditions. Firstly, a GSC-based vector control method is proposed to suppress the PCC voltage fluctuations when a large inductive load is suddenly connected. The proposed technique is based on an analytical model of the transient behaviour of the voltage drop at the PCC. To block a double fundamental frequency component as a result of reactive current compensation, a notch filter is designed. Secondly, an RSC-based vector control method is proposed using an analytical model of the voltage drop caused by a short circuit. Moreover, using a fuzzy logic controller, the proposed technique employs the voltage frequency in addition to the power winding voltage magnitude to detect LVRT conditions. The analytical model helps in reducing the power winding voltage drop while the fuzzy logic controller leads to better response and faster detection of faults. However, the reference value for reactive current compensation is analysed using an analytical model of the voltage drop at the PCC in the event of a short-circuit fault. The results obtained from MATLAB/Simulink show that the GSC-based vector control method technique can effectively reduce about 10% voltage drop at PCCs. Total Harmonics Distortion (THD) is improved to 22.3% by notch filter in comparison with an existing technique such as instantaneous reactive power theory. The RSC-based vector control method can achieve up to 11% voltage drop reduction and improve the THD by 12% compared to recent synchronous control and flux tracking methods