Novel clustering method for coherency identification using an artificial neural network
Mang-Hui Wang, Hong‐Chan Chang · IEEE Transactions on Power Systems · 1994
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.>