Advanced digital signal processing based redefined power quality indices, and their applications to wind power.

摘要

This dissertation proposes a time-frequency distribution (TFD) based new method to redefine the power quality (PQ) indices for the assessment of PQ disturbances typically present in electric power systems. The redefined PQ indices are applied to various types of synthetic and real-world PQ disturbances in order to verify the efficacy and applicability of the proposed method. The case studies show that the proposed method provides actual results with respect to the existing TFD-based transient PQ indices, and provides much more accurate results than the traditional fast Fourier transform (FFT) based PQ indices under stationary and nonstationary PQ disturbances.;In addition, utilizing the proposed method, the power components contained in the IEEE Standard 1459-2010 are redefined for single-phase, and three-phase power systems under sinusoidal, nonsinusoidal, balanced and unbalanced conditions. Unlike the traditional FFT-based method, the proposed method is able to extract the time information lost in the FFT, and provides very accurate and instantaneous assessment of the power components according to the IEEE Standard 1459-2010. Also, the proposed method will have the advantage of finding the instantaneous direction of time-varying harmonics power flow which can be positive or negative depending on the harmonics flow to the network or to the load. According to the IEEE Standard 1459-2010, the harmonic active power PH is obtained by subtracting the fundamental active power P 1 from the total active power P (PH = P -- P 1). However, the indirect measurement of the harmonic active power may provide imprecise result since harmonic active power is generally very small part of the total active power. In this dissertation, a direct assessment of the harmonic active power is carried out to obtain accurate result based on the proposed method.;In addition, a new perspective for wind power grid codes is proposed in order to verify that a wind generating plant conforms to grid codes requirements under stationary and nonstationary PQ disturbances, and to obtain supervisory data to protect system reliability. The proposed method is also able to extract the dynamic signature of PQ disturbances introduced by variable speed wind energy conversion systems onto the electrical grid. Also, a TFD-based new method is proposed for the assessment of grid frequency deviation caused by wind power fluctuations in fixed speed wind energy conversion systems.