Graphical Models in Meshed Distribution Grids: Topology Estimation, Change Detection & Limitations
Graphical Models in Meshed Distribution Grids: Topology Estimation, Change Detection & Limitations
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DOI：
10.1109/tsg.2020.2978541
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发表时间：
2020-09-01
影响因子：
9.6
通讯作者：
Salapaka, Murti V.
中科院分区：
文献类型：
--
作者：
Deka, Deepjyoti;Talukdar, Saurav;Salapaka, Murti V.
图形模型是一种表示概率分布结构的简洁方法。分析了非辐射状配电网节点电压的图形模型。利用图模型的代数和结构特性，沿着提出了准确确定配电网拓扑结构和检测线路变化的算法，并指出了其理论局限性。我们发现，如果配电网的周期/环路的大小大于三，那么节点电压是足够的有效的拓扑估计，而无需额外的假设系统参数。相比之下，使用节点电压的线路故障或变化检测不需要任何结构假设。噪声测量下，我们提供了第一个非平凡的界限上的最大噪声，系统可以容忍渐近正确的拓扑恢复。所设计的算法的性能进行了验证与非线性交流潮流样本Matpower上的测试电网，包括注入相关性和系统噪声的情况下产生的。
Graphical models is a succinct way to represent the structure of a probability distributions. This article analyzes the graphical model of nodal voltages in non-radial power distribution grids. Using algebraic and structural properties of graphical models, algorithms exactly determining topology and detecting line changes for distribution grids are presented along with their theoretical limitations. We show that if distribution grids have cycles/loops of size greater than three, then nodal voltages are sufficient for efficient topology estimation without additional assumptions on system parameters. In contrast, line failure or change detection using nodal voltages does not require any structural assumption. Under noisy measurements, we provide the first non-trivial bounds on the maximum noise that the system can tolerate for asymptotically correct topology recovery. The performance of the designed algorithms is validated with non-linear AC power flow samples generated by Matpower on test grids, including scenarios with injection correlations and system noise.