CEEMDAN algorithm-based power system low-frequency oscillation mode identification method

• Main Authors: YIN XIANGXIANG, WANG CHANGJIANG, LI BIN, QU CHAO, LI ZHENGWEN, LIANG XUYU, SU ANLONG, LIU JINGSONG, ZHANG YANJUN, GE WEICHUN, GAO KAI, LIU AIMIN, JIANG TAO, KONG JIANHONG, HAN ZIJIAO
• Format: Patent
• Language: Chinese; English
• Published: 16.04.2019
• Subjects: CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER; ELECTRICITY; GENERATION; SYSTEMS FOR STORING ELECTRIC ENERGY

The invention relates to the field of electrical engineering and particularly relates to a CEEMDAN algorithm-based power system low-frequency oscillation mode identification method. According to the method, the actual measurement data, including rotor angle signals of a generator, of a power system are acquired by utilizing a wide-area measurement system. After that, the complete-set empirical mode of the adaptive noise of each group of original low-frequency oscillation signals is decomposed into Complete Ensemble Empirical Mode Decomposition with Adaptive Noise. The CEEMDAN algorithm is decomposed into a sum of a plurality of intrinsic mode functions (Intrinsic Modes) and IMFs, and each IMF component represents an oscillation mode. The energy value and the energy weight of each IMF component are calculated. Finally, the Hilbert-Huang transform is used for identifying the oscillation frequency and the damping ratio of the dominant oscillation mode, and the calculation result is compared with a characteristic