Water Distribution - Multiobjective Optimization Visualization (wd-movis)
This repository contains the data and code associated with the manuscript titled "Optimizing Distribution Controls for Safe, Affordable, Low-Carbon Water Supply", currently in revision with Water Resources Research.
Data includes the aggregated simulation-optimization data and the electricity emissions/costing data for a complex water distribution case system.
We also provide the jupyter notebooks used to generate figures for the investigation, showing the baseline operations, domain targeting, optimization results, and a water demand analysis.
Water distribution simulations were run using the Python Package Water Network Tool for Resilience (WNTR):
Klise, K.A., Hart, D.B., Bynum, M., Hogge, J., Haxton, T., Murray, R., Burkhardt, J. (2020). Water Network Tool for Resilience (WNTR) User Manual: Version 0.2.3. U.S. EPA Office of Research and Development, Washington, DC, EPA/600/R-20/185, 82p.
Operations were optimized using the open-source package Distributed Evolutionary Algorithms in Python (DEAP):
De Rainville, F.-M., Fortin, F.-A., Gardner, M.-A., Parizeau, M., & Gagné, C. (2012). DEAP: a python framework for evolutionary algorithms. In Proceedings of the 14th annual conference companion on Genetic and evolutionary computation (pp. 85–92). New York, NY, USA: Association for Computing Machinery.
The case study hydraulic model and demand data was provided confidentially and contains protected critical infrastructure data.