A Coherency-Based Approach for Signal Selection for Wide Area Stabilizing Control in Power Systems

In this paper, a systematic procedure to select wide-area input/output control signals based on a signal coherency approach to damp out inter-area mode of oscillations is proposed. The coherent signal groups are chosen based on a data clustering approach. The input/output signal selection is carried out in two steps. First, the data is transformed into orthogonal space to make correlated variables uncorrelated, by applying principal component analysis. Then, the principal component vectors are given as input to a self-organizing map for final data clustering. From each clustered signal group, a signal out of those with common features is selected. For clustering, the data are collected from the system dynamic simulation considering few critical line contingency. The efficacy of the proposed feature selection based method is verified by comparing the results with a geometric-based approach and a pole vector direction based signal selection approach on 39-bus New England and 68-bus New England New York power systems.