电网振荡与故障识别新方案研究

A Novel Algorithm to Distinguish Swing and Fault in Power Networks

提出了一种故障与振荡信号小波识别新算法。利用小波系数局部模极大值、不同频段小波系数变化率、电流小波系数幅值变化趋势以及电流与电压小波系数相角差提出了4种振荡与故障信号小波识别新判据,并根据各判据的特点与适用性,运用模糊集合理论,形成2种综合判据。根据各判据的特点与适用性,分别将其应用于振荡闭锁装置和子站端故障与振荡信号识别系统。典型算例验证了综合判据的有效性,可望将其应用到实际电网故障诊断系统和距离继电器振荡闭锁装置。

A new scheme to distinguish swing and fault occurring in transmission lines is proposed based on wavelet transform. A new synthesized criterion consists of four methods as following： the first, comparison of the local maximum wavelet coefficients of the singularity point; the second, how those wavelet coefficients mentioned above changes in different frequency band at the very moment; the third, how those wavelet coefficients changes as time goes by in the same frequency band; the fourth, how the phase between voltage and current changes as time goes by in the same frequency band. Each method is evaluated by the performance and applicability based on fuzzy set theory. The algorithm proves to be feasible and of high veracity in typical experiments, and it is possible to apply them in fault diagnosis system and distance protection.