基于小波能量系数的主导低频振荡模式检测

摘要

A new algorithm about dominant inertial modes detection for power systems is proposed in this paper. First, empirical mode decomposition(EMD) is used to acquire main features of inertial modes from system power angle or power curves, then continuous wavelet transform is effectively applied to extract modes parameters, finally the dominant inertial modes are identified by calculation of wave energy coefficient. This method, unrestricted from the size of system, can effectively analyze and detect the dominant inertial modes of power systems, and it can overcome the defect of dimension disaster to linear eigenvalue analysis algorithm when calculate the dominant inertial modes of system. The simulation results show that this algorithm can accurately detect dominant inertial modes of power systems. The results are identical to the analytical conclusions based on normal form theory, then it is verified that this algorithm can be correctly and effectively used to detect the dominant inertial modes of power systems.%提出了一种检测电力系统主导低频振荡模式的新方法.先利用经验模态分解(EMD)从系统功角或功率曲线上获取低频振荡模式主要特征,再应用连续小波变换有效提取模态参数,最后通过计算小波能量系数识别系统主导低频振荡模式.新方法不受系统规模的限制,可以有效地分析、检测大小扰动下电力系统主导低频振荡模式,克服了线性化特征法在计算时所出现的维数灾缺点.算例结果表明,该方法能准确检测出系统主导低频振荡模式,其结果与正则形理论分析结果相同,进而验证了此方法的正确性和有效性.