Identifying causal interaction in power system: Information-based approach

Stability analysis of power system is a problem of immense importance in power community. Identification of the cause for instability is a relevant problem and has been studied widely. In this work we provide a novel approach, using the concept of information transfer in a dynamical system, to identify the states and the generators which are most responsible for instability in a given power network. Our developed notion of information transfer is physically motivated and has been previously shown to capture the true notion of causality and influence. In this paper, we use information transfer measure to characterize causal interactions and influence in a power network. In particular, we identify the dynamic states of the generators (and the generator) which are most responsible for the instability. We further determine the states which contribute most to system oscillations and these findings reflect the physical intuitions of power network. Moreover, the analysis of information transfer from generators to load identifies which generators are most responsible for load fluctuations.