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Complexity analysis of power system energy flow

机译:电力系统能流的复杂性分析

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摘要

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.
机译:对电力系统故障传播的动态行为进行研究有助于理解系统状态的演变,从而可以快速了解系统的运行状态。建立了基于电力系统动力学方程的能量函数模型,以在故障发生后提取系统能量信息。通过应用多尺度熵方法分析了演化系统能量流的复杂性。分析结果表明,故障传播的复杂度随着故障持续时间的增加而增加。与不稳定故障产生的能量流相比,稳定状态下的系统能量流复杂度已显着降低。此外,不稳定状态的系统复杂性是小时间尺度上的不确定性和大时间尺度上的规律性的结合。最重要的特征是临界稳定状态和临界不稳定状态的系统复杂性,这些复杂性在这些不同的时间尺度上明显不同。这样的差异可以用作区分临界稳定状态和临界不稳定状态的重要度量。研究结果可以为研究故障传播动态行为中的能流演化提供新的思路和方法。

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