Abstract
Hydraulic State Estimation allows to estimate the most likely state of a water supply network considering multiple sources of information and their associated uncertainty. It is set out as an optimization problem, often addressed according to the Weighted Least Squares criterion. It can be formulated differently depending on the selected set of state variables. This choice is not straightforward and leads to different problem dimensions, time complexities and convergence behavior. All possible essential approaches are gathered in this work and two are identified as the most suitable according to the resulting problem dimensions: a head-based approach and a demand-based approach. The particularities and the formulation according to both sets of state variables are discussed, seeking for efficient implementation. Their time complexity and convergence behavior are compared to draw conclusions that help to identify the most suitable approach for real practice applications.
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