Optimal sensor placement for parametric model identification of electrical networks, part I: Open loop estimation
Optimal sensor placement for parametric model identification of electrical networks, part I: Open loop estimation
复制标题
用于电网参数模型识别的最佳传感器放置，第一部分：开环估计
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
C. Martin
中科院分区：
文献类型：
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作者：
A. Chakrabortty;C. Martin
在本文中，我们提出了一种算法，用于沿着大型电振荡器网络的边缘最优地放置传感器，以识别网络的参数模型，该模型使用动态测量电信号，如电压和电流的幅度和相位角，被高斯噪声破坏。我们将识别问题视为对每条边的四个基本参数的估计，即边权的实分量和虚分量（或等效地，沿传输线的电阻和电抗），以及由这条边连接的两台机器的惯性。然后，我们为这四个未知参数的估计制定了Cramer-Rao界，并表明该界是传感器位置的函数。最后，我们陈述了寻找最优传感器位置以达到最紧的Cramer-Rao界的条件。
In this paper we present an algorithm for placing sensors optimally along the edges of a large network of electrical oscillators to identify a parametric model for the network using dynamic measurements of electrical signals such as magnitudes and phase angles of voltages and currents, corrupted with Gaussian noise. We pose the identification problem as estimation of four essential parameters for each edge, namely the real and imaginary components of the edge-weight (or, equivalently the resistance and reactance along the transmission line), and the inertias of the two machines connected by this edge. We then formulate the Cramer-Rao bounds for the estimates of these four unknown parameters, and show that the bounds are functions of the sensor locations. We finally state the condition for finding the optimal sensor location to achieve the tightest Cramer-Rao bound.