MAGNets: Model Reduction and Aggregation of Water Networks

Abstract

Hydraulic models of large water distribution networks can have thousands of components, and real-time simulation of these systems can be slowed down by their complexity. Several methods have been developed for which the size of the water network models can be reduced while the hydraulic performance of the reduced systems remains very similar to the original model. Model reduction allows users to model only components of interest, thus saving expensive computation time. However, while model reduction has been widely adopted for control and optimization purposes, few tools are available to reduce models on command. This paper introduces MAGNets, an open-source Python package capable of reducing and aggregating EPANET-compatible water models using the variable elimination reduction method. The package allows the user to specify the operating point around which the model will be reduced, the nodes that must remain in the network, and the maximum nodal degree of nodes removed. The reduced model preserves pressure heads of the original model with high accuracy and results in faster running times. The reduction algorithm iteratively removes nodes from the full model and updates the adjacent nodal demands and pipe properties until the final reduced model is achieved. To test the effect of the order of node removal on the size of the reduced model and computational complexity, we tested three different strategies for reduction order. Results suggest that dynamically updating reduction order greatly improves model performance compared to static and random orders. To increase usability, the Python package includes twelve benchmark networks for testing and validation. MAGNets allows for the quick and efficient reduction of hydraulic models as a way to facilitate time-sensitive tasks, such as real-time state estimation and control.