| 引用本文: | 位俊明,吕世轩,王 伟,等.基于改进自适应S变换的电能质量扰动实时检测方法[J].电力系统保护与控制,2025,53(14):40-48.[点击复制] |
| WEI Junming,LÜ Shixuan,WANG Wei,et al.Real time detection method for power quality disturbances based on improved adaptive S-transform[J].Power System Protection and Control,2025,53(14):40-48[点击复制] |
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| 摘要: |
| 针对复合电能质量扰动检测算法实时性差、时频分辨率低的问题，提出了一种基于改进自适应S变换(improved adaptive S transform, IAST)的电能质量扰动实时检测方法。构建全局自适应高斯窗作为IAST的核函数，可随检测频率变化自适应调整窗函数有效窗长及频谱，避免为提高时频分辨率频繁切换窗口参数，降低算法复杂度。以增强信号能量集中度为参数调优目标选取窗口参数，确保对各类扰动的精确时频定位。采用自动阈值法确定实际扰动信号的主频点，并对主频点进行时频变换，进一步提高算法执行效率。仿真和实测结果表明，相比于现有复合电能质量扰动检测算法，该检测方法实时性好、时频分辨能力强、计算复杂度低，适用于复杂电能质量扰动实时准确检测。 |
| 关键词: 电能质量扰动 自适应高斯窗 时频分析 改进S变换 |
| DOI：10.19783/j.cnki.pspc.241316 |
| 投稿时间：2024-09-28修订日期：2025-01-09 |
| 基金项目:山西省自然科学基金项目资助(202403021211215，202303021222032) |
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| Real time detection method for power quality disturbances based on improved adaptive S-transform |
| WEI Junming1,LÜ Shixuan2,WANG Wei2,ZHENG Lijun1,LIU Xin1,HU Runze1 |
| (1. Shanxi Key Laboratory of Mining Electrical Equipment and Intelligent Control (Taiyuan University of Technology), Taiyuan
030024, China; 2. State Grid Shanxi Electric Power Company Electric Power Science Research Institute, Taiyuan 030001, China) |
| Abstract: |
| Aiming at the problems of poor real-time performance and low time-frequency resolution in existing detection algorithms for composite power quality disturbances, a real-time power quality disturbance detection method based on improved adaptive S-transform (IAST) is proposed. A globally adaptive Gaussian window is constructed as the kernel function of the IAST, allowing the effective window length and frequency spectrum to adapt dynamically with the detection frequency. This avoids the need for frequent switching of window parameters to improve time-frequency resolution, thereby reducing algorithm complexity. The window parameters are optimized with the objective of enhancing signal energy concentration, ensuring accurate time-frequency positioning of various types of disturbances. An automatic thresholding method is used to determine the dominant frequency points of the actual disturbance signals, which are then subjected to time-frequency transformation to further improve computational efficiency. Simulation and experimental results show that, compared with existing algorithms for detecting composite power quality disturbances, the proposed method offers superior real-time performance, strong time-frequency resolution, and low computational complexity, making it suitable for accurate real-time detection of complex power quality disturbances. |
| Key words: power quality disturbance adaptive Gaussian window time-frequency analysis improved S-transform |
