Flood regulation using nonlinear model predictive control (original) (raw)
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Flood Regulation by Means of Model Predictive Control
In this chapter flooding regulation of the river Demer is discussed. The Demer is a river located in Belgium. In the past the river was the victim of several serious flooding events. Therefore, the local water administration provided the river with flood reservoirs and hydraulical structures in order to be able to better manage the water flows in the Demer basin. Though this measures have significantly reduced the floods in the basin, the recent floods in 1998 and 2002 showed that this was not enough. In order to improve this situation a pilot project is started with as main goal to regulate the Demer with a model predictive controller. In this chapter the results of this project are discussed. First a simplified model of the Demer basin is derived based on the reservoir model. The model is calibrated and validated using historical data obtained from the local water administration. On the one hand the resulting model is accurate enough to capture the most important dynamics of the river; on the other hand the model is fast enough to be used in a real-time setting. Afterwards, the focus will be shifted to the model predictive controller. The use of the model predictive controller will be justified by comparing it to other control strategies used in practice for flood regulation. Then, the more technical details of the model predictive controller will be discussed in more detail. Finally the chapter will be concluded by historical simulations in which the model predictive controller is compared with the current control strategy used by the local water administration.
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Managing a multi-reservoir system is complicated, due to conflicting interests among various objectives. This study proposes an optimization-based approach for the operations of a multi-reservoir system. An advanced real-time control technique, Model Predictive Control (MPC), is adopted to control a multi-reservoir system with two control objectives, i.e., flood mitigation and water conservation. The case study area is the Sittaung River basin in Myanmar, where the current reservoir operating rule needs to be improved for a more effective operation. A comparison between an MPC-based operation and the current operation is presented by using performance indicators. The result shows a reduction of the system’s vulnerability by 0.9 percent using MPC. Due to the physical constraint of the reservoirs, it is impossible to completely eliminate the flood risk at Taungoo City during high inflow events. However, the results indicate that the potential flood risk can be mitigated by improving t...
Flooding prevention of the demer river using model predictive control
Proceedings of the …, 2008
Flooding Prevention of the Demer River using Model Predictive Control Toni Barjas Blanco, ∗,1 Patrick Willems, ∗∗ Bart De Moor, ∗ Jean Berlamont ∗∗ ... ACKNOWLEDGEMENTS Toni BarjasBlanco is a research assistant at the Katholieke Universiteit Leu-ven, Belgium. ...
Model Predictive Control for optimising the operation of Urban Drainage Systems
This work presents a methodology for developing a Model Predictive Control (MPC) for enhancing the operation of Urban Drainage Systems (UDS). The objective of the MPC is to apply a proactive management strategy that uses optimised time-state schedules for operating the actuators of UDS in real time. Aiming to mitigate flooding consequences, the MPC uses EPA-SWMM hydrologic-hydraulic simulation engine and Genetic Algorithm (GA) to optimise the time-state schedules for the actuators of UDS. The efficiency of the MPC was tested on the Lille University Campus, resulting in satisfying improvements in the use of storage capacity of retention elements within the UDS.