Living and Prototyping Digital Twins for Urban Water Systems: Towards Multi-Purpose Value Creation Using Models and Sensors

Abstract

In this paper, we review the emerging concept of digital twins (DTs) for urban water systems (UWS) based on the literature, stakeholder interviews and analyzing the current DT implementation process in the utility company VCS Denmark (VCS). Here, DTs for UWS are placed in the context of DTs at the component, unit process/operation or hydraulic structure, treatment plant, system, city, and societal levels. A UWS DT is characterized as a systematic virtual representation of the elements and dynamics of the physical system, organized in a star-structure with a set of features connected by data links that are based on standards for open data. This allows the overall functionality to be broken down into smaller, tangible units (features), enabling microservices that communicate via data links to emerge (the most central feature), facilitated by application programing interfaces (APIs). Coupled to the physical system, simulation models and advanced analytics are among the most important features. We propose distinguishing between living and prototyping DTs, where the term “living” refers to coupling observations from an ever-changing physical twin (which may change with, e.g., urban growth) with a simulation model, through a data link connecting the two. A living DT is thus a near real-time representation of an UWS and can be used for operational and control purposes. A prototyping DT represents a scenario for the system without direct coupling to real-time observations, which can be used for design or planning. By acknowledging that different DTs exist, it is possible to identify the value-creation from DTs achieved by different end-users inside and outside a utility organization. Analyzing the DT workflow in VCS shows that a DT must be multifunctional, updateable, and adjustable to support potential value creation across the utility company. This study helps clarify key DT terminology for UWS and identifies steps to create a DT by building upon digital ecosystems (DEs) and open standards for data.

The Bellinge data set: open data and models for community-wide urban drainage systems research

“…The distributed urban drainage model was made by VCS in the MU software system (DHI, 2020) and is part of an operation 315 model that is run and compared with obervations on a routine basis as part of a digital twin environment currently under development (Pedersen et al, 2021b). The hydrodynamic model consists of around 1000 nodes and 51 km of pipes (40 km combined sewer pipes, 7 km separate stormwater pipes, and 4 km wastewater pipes, see Figure 1B), and the surface module consists of 713 individual sub-catchments with sizes up to 10 ha with median size on 0.3 ha.…”

“…Time 55 series of observations of levels and flows in the system will also be necessary for many investigations of e.g., model calibration techniques (Krebs et al, 2013;Vonach et al, 2019), development of improved skill scores (Bennett et al, 2013), uncertainty analysis (Deletic et al, 2012), techniques for data quality control (Kirstein et al, 2019;Therrien et al, 2020), development of data-driven models and machine learning (Carbajal et al, 2017;Eggimann et al, 2017;Palmitessa et al, 2021) and software sensors (Fencl et al, 2019). Other areas that can be inspired by open data sharing could be the construction of digital ecosystems 60 (Sarni et al, 2019) and digital twins (Pedersen et al, 2021b;Therrien et al, 2020). The more complete and more diverse the data set is (spatially and temporally), the more research potential there will be.…”

“…10 years). VCS mainly uses sensor data for day-to-day operation and planning of maintenance work, but also for developing a digital twin strategy (Pedersen et al, 2021b). In cases where a sensor has limited effect on the system control, longer periods with missing data may occur as those data are not a high priority (e.g., one of the duplicate sensors at G71F04R).…”

Digital Twins in Civil Infrastructure Systems

“…Urban water systems are complex, with a large extent of components residing underground. These are difficult to monitor during operation and, in the event of failure, complicated to repair [60]. Further complexity arises from fluctuations in rainfall and the fact that surface runoff depends on past weather events as well as population growth, resource scarcity and infrastructure wear and tear [33].…”

From soft sensing to anomaly detection in combined sewer systems

“…Depending on the type of model, the soft sensor can be localized in space or cover large portions of the UDS. Examples of both types are reported in the literature, including a CFD-derived model for the monitoring of a combined sewer overflow (Ahm et al, 2016) and a system-wide digital twin of the urban drainage system for model-based real-time monitoring of the whole network (Pedersen et al, 2021).…”