Bio-inspired Optimization Strategy for Identify Coherent Nonlinear Generators Response

Coherency identification is one of the key steps to carrying out different control system strategies to avoid a partial or complete blackout of a power system. However, the oscillatory trends and the non-linear dynamic behaviour of the system measurements in the first seconds of the transient period often mislead the appropriate knowledge of the actual coherent groups, making wide-area coherency monitoring a challenging task. Inspired by swarm behavior in nature, we propose a modified Particle Swarm Optimization (PSO) approach based on centroids codification to identify coherency within a short observation window. A user-defined inter-group function is proposed and compared with conventional intra-group functions to examine the quality of the compacting and separating features of the final clusters. To demonstrate the effectiveness of our technique, we clustered the highly nonlinear dynamic responses of the generators on the 39-bus New England system. A comparison with other clustering methods was carried out to highlight the strength of the proposed algorithm.