Highlights  Integrated pollution-based real-time control can reduce pollute of sanitation system.  Model predictive control with quality dynamics generates optimal control strategy.  Feedback coordination algorithm integrates subsystems during the control process.  Closed-loop virtual-reality simulator accesses effectiveness of the control strategy.  A real life pilot is used to demonstrate applicability of the proposed approaches.

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This paper presents a complete methodology for the development of an integrated software architecture, which can achieve a closed-loop application between the integrated real-time control (RTC) and a virtual reality simulation for the urban drainage system (UDS). Quality measurements are considered during the simulation and optimization process. Model predictive control (MPC) and rule-based control (RBC) are the two main RTC methods embedded in this architecture. The proposed integration environment allows the different software components to efficiently and effectively communicate and work in a system-wide way, as well as to execute all the necessary steps regarding input parameters management, scenario configuration and results extraction. The proposed approaches are implemented into a pilot based on the Badalona UDS (Spain). Results from different scenarios with individual control approaches and rain episodes are evaluated and discussed.

The worldwide growing demand of water supply requires a proper management of the available hydraulic resources. One of the major concerns in the operation of water distribution networks (WDNs) is the existence of leakages, due to the high operational costs for the water utilities. Leaks can produce substantial economic losses, infrastructure damage and even health risks. Therefore, leak detection and isolation methodologies are widely researched.One the one hand, model-based approaches exploit the existence of a hydraulic model of the considered WDN, as well as the availability of hydraulic measurements like inlet flow and pressure, and sensorized inner nodes pressure, to tackle the leak localization task. The suitability of these methods has been confirmed by numerous works during the years. On the other hand, the sources of information in the majority of water networks are rather limited, and other interesting measurements are not available, like water demands at the junctions, flows between inner nodes, etc. Thus, datadriven approaches, which have a reduced or non-existent dependency on a hydraulic model, can be helpful to locate leaks in WDNs that lack the mentioned measurements and modelling. This abstract presents the combined utilization of a model-based and a novel data-driven methodology to locate leaks in the concrete case of the challenge proposed at BattLeDIM 2020. The division of the introduced network (L-Town) in three areas allows to determine the usage of one of the approaches at each one of these areas, depending on their concrete characteristics.Besides, both methods allow to solve the multi-leak problem in a proper way, which entails a further step with regard to the classical single-leak assumption.