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Inverter Probing for Power Distribution Network Topology Processing

机译:配电网拓扑处理的逆变器探测

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Knowing the connectivity and line parameters of the underlying electric distribution network is a prerequisite for solving any grid optimization task. Although distribution grids lack observability and comprehensive metering, inverters with advanced cyber capabilities currently interface solar panels and energy storage devices to the grid. Smart inverters have been widely used for grid control and optimization, yet the fresh idea here is to engage them towards network topology inference. With an electric circuit, a distribution grid can be intentionally probed by instantaneously perturbing inverter injections. Collecting and processing the incurred voltage deviations across nodes can potentially unveil the grid topology even without knowing loads. Using grid probing data and under an approximate grid model, the tasks of topology recovery and line status verification are posed, respectively, as nonconvex estimation and detection problems. Leveraging the features of the Laplacian matrix of a tree graph, probing terminal nodes is analytically shown to be sufficient for exact topology recovery if voltage data are collected at all buses. The related nonconvex problems are surrogated to convex ones, which are iteratively solved via closed-form updates based on the alternating direction method of multipliers and projected gradient descent. Numerical tests on benchmark feeders demonstrate that grid probing can yield line status error probabilities of 10(-3)( )by probing 40% of the nodes.
机译:了解基础配电网络的连通性和线路参数是解决任何电网优化任务的先决条件。尽管配电网缺乏可观察性和全面的计量功能,但具有先进网络功能的逆变器目前将太阳能电池板和储能设备连接到电网。智能逆变器已被广泛用于电网控制和优化,但是这里的新主意是使它们参与网络拓扑推理。利用电路,可以通过瞬时扰动逆变器注入来故意探测配电网。即使不知道负载,收集和处理节点之间发生的电压偏差也有可能揭示电网拓扑。使用网格探测数据并在近似网格模型下,拓扑恢复和线路状态验证的任务分别构成为非凸估计和检测问题。利用树形图的拉普拉斯矩阵的特征,如果在所有总线上收集电压数据,则分析性地显示探测终端节点足以实现精确的拓扑恢复。相关的非凸问题被代之以凸问题,这些问题通过基于乘法器交替方向方法和投影梯度下降的闭式更新迭代解决。在基准馈线上的数值测试表明,通过探测40%的节点,网格探测可以产生10(-3)()的线路状态误差概率。

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