To study the stability of dynamic systems, it is neither practical nor necessary to model the entire interconnected system in details. In more specific application, such as dynamic security assessment and system control design, reduced order models of the entire system,
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To study the stability of dynamic systems, it is neither practical nor necessary to model the entire interconnected system in details. In more specific application, such as dynamic security assessment and system control design, reduced order models of the entire system, or part of it, are needed to satisfy computational or design constraints. In this paper, a dynamic reduction method based on coherency concept is developed and slow coherency identification is used to identify coherency machine. Despite its simplicity, the proposed method provides an effective approach to recognize coherence generators. Furthermore, a new clustering method is suggested in this paper to improve acceleration of coherence machines identification. Finally, the accuracy of proposed method is evaluated by time domain simulation and compared with other methods. The obtained results indicate that the new proposed grouping method works more quickly than the other methods in the area, concluding that, without loss of accuracy, it can be readily used in dynamic studies of power systems.
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