CC BY 4.0Bernard, ThomasThomasBernardDeuerlein, Jochen W.Jochen W.DeuerleinDresen, MartinMartinDresenFischer, MichaelMichaelFischerGuth, NicolaiNicolaiGuthHöche, RüdigerRüdigerHöcheKühnert, ChristianChristianKühnertMastaller, ChristaChristaMastallerRappold, GerhardGerhardRappoldSchlolaut, GordonGordonSchlolautWunsch, AndreasAndreasWunschZiebarth, MathiasMathiasZiebarth2024-10-222024-10-222024https://publica.fraunhofer.de/handle/publica/477902https://doi.org/10.24406/h-47790210.3390/engproc202406909410.24406/h-477902Climate change is leading to a general shortage of raw water availability combined with more pronounced seasonality and dry phases. The goal of the collaborative research project TwinOptPRO is to contribute to EU-wide climate neutrality in 2050 by the minimization of energy supply for water treatment and pumps in drinking water distribution systems. For that purpose, a digital platform that combines different forecasting models with simulation and optimization modules was developed. The aim is to ensure secure and compliant supply to customers in the future while maximizing the use of renewable energy and minimizing costs.enpump schedulingbi-level optimizationhydrologydemand forecastneural networksjournal article