Efficient river management is essential in improving water resource utilisation. However, river flows and water-levels are affected by unregulated in- and out-flows. Therefore, it is important to consider the forecasts of these unregulated flows and the uncertainties in the forecasts. The paper describes control and modelling tools from the literature that suit the river management problem. Specifically, a scenario-based Stochastic Model Predictive Control (MPC) strategy, that makes use of ensemble forecast of unregulated flows, is proposed, where the ensemble forecast contains multiple flow scenarios to characterise future flows and their uncertainties, and are obtained from catchment hydrological models.

Efficient River Management using Stochastic MPC and Ensemble Forecast of Uncertain In-flows

Algo Carè;
2018-01-01

Abstract

Efficient river management is essential in improving water resource utilisation. However, river flows and water-levels are affected by unregulated in- and out-flows. Therefore, it is important to consider the forecasts of these unregulated flows and the uncertainties in the forecasts. The paper describes control and modelling tools from the literature that suit the river management problem. Specifically, a scenario-based Stochastic Model Predictive Control (MPC) strategy, that makes use of ensemble forecast of unregulated flows, is proposed, where the ensemble forecast contains multiple flow scenarios to characterise future flows and their uncertainties, and are obtained from catchment hydrological models.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/504725
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