This paper contributes a novel High-Performance Integrated Control framework to support the real-time operation of urban water supply storages affected by water quality problems. We use a 3-D, high-fidelity simulation model to predict the main water quality dynamics and inform a real-time controller based on Model Predictive Control. The integration of the simulation model into the control scheme is performed by a model reduction process that identifies a low-order, dynamic emulator running 4 orders of magnitude faster. The model reduction, which relies on a semiautomatic procedural approach integrating time series clustering and variable selection algorithms, generates a compact and physically meaningful emulator that can be coupled with the controller. The framework is used to design the hourly operation of Marina Reservoir, a 3.2 Mm3 storm-water-fed reservoir located in the center of Singapore, operated for drinking water supply and flood control. Because of its recent formation from a former estuary, the reservoir suffers from high salinity levels, whose behavior is modeled with Delft3D-FLOW. Results show that our control framework reduces the minimum salinity levels by nearly 40% and cuts the average annual deficit of drinking water supply by about 2 times the active storage of the reservoir (about 4% of the total annual demand). Key Points: A novel computational framework to real-time operation of urban reservoirs The approach combines model reduction and model predictive control Water quality and drinking supply are optimized with an hourly frequency.
CITATION STYLE
Galelli, S., Castelletti, A., & Goedbloed, A. (2015). High-Performance Integrated Control of water quality and quantity in urban water reservoirs. Water Resources Research, 51(11), 9053–9072. https://doi.org/10.1002/2015WR017595
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