基于多尺度熵的电力能量流复杂性分析

电力能量流复杂性主要体现于其动态行为的实时性、非线性及不确定性等,网络动力学行为分析是关键.本文在电力系统动力学平衡方程基础上,构建了系统势能与支路势能函数模型;通过提取扰动(或故障)后系统的能量信息,利用多尺度熵对扰动(或故障)后系统能量流演化过程进行了研究.结果表明:1)稳定运行状态下系统复杂度较低,且随着故障持续时间的增加,系统故障后呈现出更高的复杂度;2)不稳定运行状态下,系统在小尺度时间上表现出更强的不确定性,而在大尺度时间上表现出相对更明显的规则性;3)临界稳定运行状态与临界不稳定运行状态下,故障后的系统复杂度在不同时间尺度上呈现出较明显的差异,这对动态过程中临界点的识别有着积极的参考价值.本文研究揭示了电力能量流在物理动态过程中的演化机制,为电力系统动力学行为分析提供了新思路与新方法.

Complexity analysis of power system energy flow based on multi-scale entropy

Complexity of power system energy flow is mainly reflected in the features of dynamic behavior such as real-time, nonlinear, uncertainty, etc. The analysis of dynamics on network is a critical means. The potential energy function models of system and branches are established, which are based on power system dynamic equilibrium equation to extract the system energy information after the fault duration. And the complexity of the system energy flow evolution is analyzed by using the multi-scale entropy method. The analysis results show that the system complexity under steady operation is much low. In addition, the complexity of the fault system increases with the increase of fault duration. Moreover, the system complexity under unstable operation shows a strong uncertainty in a small time scale and obvious regularity in a large time scale. And the most important is that the system complexities of the critical stable state and the critical unstable state are clearly distinct in different time scales. Such a difference can be used as a positive reference to the identification of the critical point in the dynamic state. Research results reveal the evolution of power energy flow in physical dynamic process. This can provide new ideas and methods for analyzing the dynamics behavior of power system.
Keywords： power system energy flow dynamics on networks multi-scale entropy complexity analysis