电力系统的盲拓扑辨识

Xiao Li, H. Poor, A. Scaglione
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引用次数: 47

摘要

本文研究了仅利用各母线上的功率注入数据的电力系统的盲拓扑识别问题。随着计量在智能电网中的普及,一个自然的问题是,从这些数据中可以推断出多少关于底层基础设施的信息。研究了网格拓扑的可辨识性,提出了一种估计网格拉普拉斯矩阵(即网格导纳矩阵的图等价)的高效学习算法。最后,对该算法在IEEE-14总线系统中的性能进行了验证,并通过仿真验证了恢复图与底层电网关联的真图的一致性。
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Blind topology identification for power systems
In this paper, the blind topology identification problem for power systems only using power injection data at each bus is considered. As metering becomes widespread in the smart grid, a natural question arising is how much information about the underlying infrastructure can be inferred from such data. The identifiability of the grid topology is studied, and an efficient learning algorithm to estimate the grid Laplacian matrix (i.e., the graph equivalent of the grid admittance matrix) is proposed. Finally, the performance of our algorithm for the IEEE-14 bus system is demonstrated, and the consistency of the recovered graph with the true graph associated with the underlying power grid is shown in simulations.
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