基于异步测量的动态电网状态估计

G. Cavraro, E. Dall’Anese, A. Bernstein
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引用次数: 11

摘要

由于可再生能源的快速变化以及因此产生的净负荷状况,配电网的运行变得越来越不稳定。为了在这些条件下进行可靠的状态估计,本文考虑了实时收集和处理来自仪表、相量测量单元和分布式能源的测量数据以产生快速时间尺度的状态估计的情况。以异构速率实时收集的测量流使得底层处理异步,并对主力机状态估计算法造成严重压力。在这项工作中,提出了一种实时状态估计算法,该算法对数据进行动态处理。从正则化最小二乘模型出发,利用适当的线性模型,将所提出的方案归结为基于先前估计和从几个可用传感器收集的测量值更新状态的线性动态系统。在温和条件下,估计误差总是有界的。数值模拟证实了分析结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic Power Network State Estimation with Asynchronous Measurements
The operation of distribution networks is becoming increasingly volatile, due to fast variations of renewables and, hence, net-loading conditions. To perform a reliable state estimation under these conditions, this paper considers the case where measurements from meters, phasor measurement units, and distributed energy resources are collected and processed in real time to produce estimates of the state at a fast time scale. Streams of measurements collected in real time and at heterogenous rates render the underlying processing asynchronous, and poses severe strains on workhorse state estimation algorithms. In this work, a real-time state estimation algorithm is proposed, where data are processed on the fly. Starting from a regularized least-squares model, and leveraging appropriate linear models, the proposed scheme boils down to a linear dynamical system where the state is updated based on the previous estimate and on the measurement gathered from a few available sensors. The estimation error is shown to be always bounded under mild condition. Numerical simulations are provided to corroborate the analytical findings.
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