Implementing a digital twin for optimized real-time control of Gothenburg's regional sewage system

Abstract

The emerging challenges facing the City of Gothenburg and surrounding municipalities include the impacts of a variable climate, rapid growth and urbanization, aging infrastructure and changing community values and customer expectations. A digital twin (DT), based on the Future City Flow (FCF) platform, was created for the catchment to address many of these challenges in terms of improved real-time sewerage performance and predictability in the face of storms, improved DT visualization of the regional sewage transport system for operators and greater responsiveness to avoid service interruption. The FCF-based DT provides a sound base for modelling, simulating, forecasting and controlling the catchment. The versatility of the FCF DT makes it useful for gaining insight into catchment dynamics and the simulator can be used to study the effects of different scenarios or changes in the catchment. The predictive control imbedded in the FCF DT recommends setpoints for controlling the catchment that can be used by the operators for decision support or even be directly applied in the control system as model-based predictive control. A DT requires good quality online data from the catchment and, perhaps most importantly, high-quality rain forecasts, especially when prognosing long time horizons. HIGHLIGHTS Digital twins provide a sound base for modelling, simulating, forecasting, and controlling wastewater catchments.; A digital twin needs good-quality online data from the catchment.; High-quality rain forecasts are very important, especially when prognosing over long time horizons.; The model-based predictive control recommends setpoints for controlling the catchment that can be used in an advisory capacity or directly applied.;

Keywords

• collection systems
• digital twins
• optimization
• real-time control