Complexity analysis of power system energy flow

Research on the dynamic behavior of power system fault propagation is useful for understanding the evolution of system states, which can yield rapid awareness of the system operation state. An energy function model is established, which is based on power system dynamic equations, to extract the system energy information after a fault occurrence. The complexity of the evolving system energy flow is analyzed by applying the multi-scale entropy method. The analysis results show that the complexity of the fault propagation rises with the increasing fault duration time. The system energy flow complexity of a stable state is shown to be measurably reduced as compared to that produced by unstable faults. Moreover, the system complexity of unstable states is a combination of uncertainty during small time scales and regularity on large time scales. The most important features are the system complexities of the critical stable state and the critical unstable state, which are clearly distinct on these different time scales. Such a difference can be used as an important metric to distinguish the critical stable state and the critical unstable state. Research results can provide new ideas and methods for investigating the power energy flow evolution with respect to the dynamic behaviors of fault propagation.