Research On Analysis Method Of Transient Power Quality Disturbance For Power System With Wind Energy Generation

With the development of wind power technology, wind power has become a very important part in the power system. Due to the randomness and uncertainty of wind power resources, large-scale wind power on power systems will inevitably have a significant impact on the stability, economy, and security of power grid. The detection and identification of power quality of wind power system is an important basis to evaluate the quality of power supply, and it is also the basis of analysis, control and improvement of power supply. It has a very important and practical significance.Due to the difficulty of simulating the actual operation experiment of wind power system, considering the needs of real-time and accuracy of the simulation, a reliable real-time digital simulation model is built based on RTDS platform. The model adopts variable direct-driven permanently wind turbine-generators. Based on this model, the transient power quality disturbance signals caused when wind power system performs switching operations and short circuit faults appears are obtained, which include voltage sag, voltage swell, voltage interrupt, transient oscillation and complex disturbance data.Aiming at the power quality disturbance detection, considering that modal aliasing problem exists in empirical mode decomposition when processing the power system transient power quality disturbances, a simple and efficient method, i.e. high-frequency harmonic injection based EMD (HF-EMD), is proposed to improve it. The effectiveness of this method depends on the selection of the high-frequency harmonic frequency, and there is no effective frequency selection principle. Focusing on this problem, this paper conducts a systematic study. Through theoretical analysis and simulation test, a concrete and effective selection principle is presented. By combining the analysis of power quality signals simulated, the analysis of actual complex disturbance signals of substation and the detection of transient power quality disturbances in wind power system, the universality and effectiveness of HF-EMD are verified.Aiming at the combined power quality disturbance recognition, an automated recognition method based on wavelet packet entropy (WPE) and modified incomplete S-transform (MIST) is proposed in this paper. To begin with, by combining wavelet packet Tsallis singular entropy, energy entropy and MIST,13 vectors of power quality (PQ) disturbances including single disturbances and combined disturbances are extracted. Then, a ruled decision tree is designed to recognize the combined disturbances. The proposed method is tested and evaluated using a large number of simulated PQ disturbances and some real-life signals, which include voltage sag, swell, interruption, oscillation transient, impulsive transient, harmonics, voltage fluctuation and their combinations. And the comparison of the proposed recognition approach with some existing techniques is made. The experimental results illustrate that the proposed method can effectively recognize the single and combined PQ disturbances. At the same time, it is applied in the identification of transient power quality disturbances of the wind power system, which verifies the validity of the method.