Sensor Placement and State Estimation in Water Distribution Systems Using Edge Gaussian Processes
Bulat Kerimov (Norwegian University of Science and Technology (NTNU))
Vincent Pons (Norwegian University of Science and Technology (NTNU))
Spyros Pritsis (Norwegian University of Science and Technology (NTNU))
Riccardo Taormina (TU Delft - Sanitary Engineering)
Franz Tscheikner-Gratl (Norwegian University of Science and Technology (NTNU))
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
The operation of water distribution systems is based on reliable knowledge about the steady state of the system. This involves sensors to measure flow, facilitating a comprehensive overview of the system’s performance. Given the costs associated with sensor installation and operation, it is important to be strategic with sensor allocation. Recently developed Gaussian Processes with topological kernels can efficiently model mass and energy conservative flows and provide uncertainty bounds. Our work proposes a novel method of state estimation and a greedy search algorithm for water flow meter placement based on the uncertainty bounds provided by a Gaussian Process.
help_outline