Abstract:Accurate estimates of network parameters are essential for modeling, monitoring, and control in power distribution systems. In this paper, we develop a physics-informed graphical learning algorithm to estimate network parameters of threephase power distribution systems. Our proposed algorithm uses only readily available smart meter data to estimate the threephase series resistance and reactance of the primary distribution line segments. We first develop a parametric physics-based model to replace the black-box… Show more
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