{'fraction_non_alphanumeric': 0.015536723163841809, 'fraction_numerical': 0.002824858757062147, 'mean_word_length': 5.354260089686099, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Generator Coherency and Network Partitioning for Dynamic Equivalencing Using Subtractive Clustering Algorithm

In this paper, a new method called subtractive clustering is presented to partition a power system into areas after a disturbance occurs. Subtractive clustering is basically used as a preprocessing step for other clustering methods to overcome their shortcomings, such as the need to predefine the number of areas and high dependency to random functions. However, due to the special characteristics of power systems, this method itself can be used to find areas. In subtractive method, the degree of coherency between all buses is used to form a density value for each bus. To calculate the degree of coherency between buses, the frequency components existing in the angular velocity variation of voltage phasors, in the range of interarea and local oscillation modes, are extracted. Then, the correlation between the real parts of these frequencies and the correlation between the imaginary parts are calculated individually. This means that the coherency between each pair of buses is assessed in two dimensions, which results in more efficient dynamic coherency identification. The capability of the proposed method is demonstrated for disturbances applied on the 16-machine, 68-bus system. It is observed that subtractive method is highly appropriate to find coherent areas for different disturbances.