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PQ decoupled 3‐phase numerical observability analysis and critical data identification for distribution systems

机译:配电系统的PQ解耦三相数值可观性分析和关键数据识别

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摘要

Emerging active distribution systems are operated under more complicated and uncertain conditions. Because of frequent topology changes or temporary malfunctions of data acquisition, the network may lose observability and in turn may lead to the failure of distribution system state estimation. Without distribution system state estimation, the distribution system operator may not be able to make secure decisions, and the system may face with risk of serious damages. In this paper, a new real/reactive (PQ) decoupled 3‐phase numerical observability analysis method and a new critical data identification method for distribution systems are proposed. The methods can efficiently identify all unobservable branches and critical data in a non‐iterative manner. In addition to the 3‐phase decoupling, the normal equation is also PQ decoupled, and the computation burden is greatly reduced. Furthermore, all entries in the Jacobian matrix are non‐negative integers and the proposed methods present good numerical performance. Strict theoretical proofs on the performance of the proposed methods are provided and numerical results on different scales of test systems illustrate their validities.
机译:新兴的主动配电系统在更加复杂和不确定的条件下运行。由于频繁的拓扑更改或数据采集的临时故障,网络可能会失去可观察性,进而可能导致配电系统状态估计失败。如果没有配电系统状态估计,则配电系统操作员可能无法做出安全的决策,并且系统可能面临严重损失的风险。提出了一种新的PQ解耦的三相数值可观性分析方法和一种新的配电系统关键数据识别方法。这些方法可以以非迭代方式有效地识别所有不可观察的分支和关键数据。除三相解耦外,正常方程式也经过PQ解耦,大大减轻了计算负担。此外,雅可比矩阵中的所有条目都是非负整数,并且所提出的方法具有良好的数值性能。提供了对所提出方法的性能的严格理论证明,并且在不同规模的测试系统上的数值结果证明了它们的有效性。

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