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

Abstract

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

    Similar works