Enhancing observability in power distribution grids

Siddharth Bhela, V. Kekatos, Liang Zhang, S. Veeramachaneni
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引用次数: 10

Abstract

Power distribution grids are currently challenged by observability issues due to limited metering infrastructure. On the other hand, smart meter data, including local voltage magnitudes and power injections, are collected at grid nodes with renewable generation and demand-response programs. A power flow-based approach using these data is put forth here to infer the unknown power injections at non-metered grid nodes. Exploiting the control capabilities of smart inverters and the relative time-invariance of conventional loads, the idea is to solve the non-linear power flow equations jointly over two system realizations. An intuitive condition pertaining to the graph of the underlying grid is shown to be necessary and sufficient for the local identifiability of this task. The derived graph theoretic criterion can be checked efficiently and is numerically verified under realistic scenarios on the IEEE 13-bus feeder.
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提高配电网的可观测性
由于计量基础设施有限,配电网目前面临着可观测性问题的挑战。另一方面,智能电表数据,包括当地电压大小和电力注入,是在可再生能源发电和需求响应程序的电网节点收集的。本文提出了一种基于潮流的方法,利用这些数据来推断非计量电网节点的未知功率注入。利用智能逆变器的控制能力和传统负载的相对时不变性,其思想是在两种系统实现上联合求解非线性潮流方程。一个与底层网格图形相关的直观条件对于该任务的局部可识别性是必要和充分的。推导的图论判据能够有效地进行校核,并在IEEE 13总线馈线的实际场景下进行了数值验证。
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