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Novel clustering method for coherency identification using an artificial neural network

Journal Article · · IEEE Transactions on Power Systems (Institute of Electrical and Electronics Engineers); (United States)
DOI:https://doi.org/10.1109/59.331469· OSTI ID:6887013
;  [1]
  1. National Taiwan Inst. of Tech., Taipei (Taiwan, Province of China). Dept. of Electrical Engineering

A novel clustering method using an artificial neural network (ANN) is presented to identify the coherent generators for dynamic equivalents of power systems. First, a new frequency measure is devised to indicate the degree of coherency among system generators. Incorporating with the frequency measure, a neural network implementation of the K-means algorithm is then proposed to identify clusters of coherent generators. The rotor speeds at three selected instants in time are used as the feature patterns for the learning algorithm. To verify the effectiveness of the proposed method, extensive analyses are performed on two different power systems of varying sizes with rather encouraging results.

OSTI ID:
6887013
Journal Information:
IEEE Transactions on Power Systems (Institute of Electrical and Electronics Engineers); (United States), Journal Name: IEEE Transactions on Power Systems (Institute of Electrical and Electronics Engineers); (United States) Vol. 9:4; ISSN ITPSEG; ISSN 0885-8950
Country of Publication:
United States
Language:
English