Pierre-Olivier Malaterre

Optimal Operation of the Multireservoir System in the Seine River Basin Using Deterministic and Ensemble Forecasts

AbstractThis article investigates the improvement of the operation of a four-reservoir system in the Seine River basin, France, by use of deterministic and ensemble weather forecasts and real-time control. In the current management, each reservoir is operated independently from the others and following prescribed rule-curves, designed to reduce floods and sustain low flows under the historical hydrological conditions. However, this management system is inefficient when inflows are significantly different from their seasonal average and may become even more inadequate to cope with the predicted increase in extreme events induced by climate change. In this work, a centralized real-time control system is developed to improve reservoirs operation by exploiting numerical weather forecasts that are becoming increasingly available. The proposed management system implements a well-established optimization technique, model predictive control (MPC), and its recently modified version that can incorporate uncertainti...

Automatic tuning of robust PI controllers for a cascade of rivers or irrigation canals pools

This paper proposes an automatic method to tune a series of distant downstream PI controllers for a cascade of pools. The methodology we present could also be used for local upstream controllers, with minor changes. Examples of such systems are irrigation canals or rivers with a series of dams and hydropower plants, such as the Rhône river in France. The method is based on the Auto-Tuned Variation principle (ATV) carrying out a relay experiment. The information obtained from this experiment allows to estimate the critical gain and critical frequency of each canal pool. This information is also used to estimate the parameters of a simplified integrator-delay model of each canal pool. Finally this allows tuning PI controllers, with given gain and phase robustness margins. This relay experiment is performed for each pool of the canal, on sequence, with automatic activation of the previously tuned PI controllers, in order to tune each distant downstream controllers in series. The method is evaluated in simulation on a bench-mark canal of 5-pools in series.

Uncertainty Quantification for River Flow Simulation Applied to a Real Test Case: The Garonne Valley

Sensitivity analysis techniques have been widely used in multitude of applications to quantify the impact of inputs variables imprecision on the accuracy of the model output variables. Depending on the problem at hand, an appropriate method of sensitivity analysis should be selected. Direct and adjoint sensitivity analysis are two complementary approaches known to be efficient. While the direct approach provides an assessment of the propagation of the error of a given input parameter in the studied system, the adjoint approach enables to identify the source of the uncertainty of a given output variable with respect to several input parameters. Direct methods have been extensively investigated in different geophysical applications, particularly in the context of the hydraulic modeling. In this work, several methods will be described and applied to the same benchmark during over-flooding events. The effect of uncertainties in the boundary conditions, the spatially distributed functions (bed level, river width, friction, etc.) and the numerical parameters on the model state variables (discharge, water surface elevation, etc.) is examined. This study has been carried out on the Garonne River test case, along a 50 km downstream reach, using 1D full Saint-Venant hydraulic models SIC2 (Irstea) or Mascaret (EDF), and 2D Telemac model (EDF). Results illustrate the influence of individual and combined contributions of input variables uncertainties.

Erratum for “Optimal Operation of the Multireservoir System in the Seine River Basin Using Deterministic and Ensemble Forecasts” by A. Ficchì, L. Raso, D. Dorchies, F. Pianosi, P.-O. Malaterre, P.-J. Van Overloop, and M. Jay-Allemand

Fig. 5. Performance of the MPC operation with perfect forecasts (PF), deterministic forecasts (DF), and ensemble forecasts (EF) over a flood event in 2007, averaged over monitoring stations: (a) loss in performance due to forecast uncertainty (with respect to perfect forecasts); (b) total number of days with violation of the (alert) thresholds; (c) mean duration of violation events; (d) maximum duration of violation events; (e) maximum flow exceedance with respect to the alert thresholds; (f) number of monitoring stations with at least one violation event over the simulation horizon

Implementation and comparison of different alternatives to remove steady state errors in a time-domain ℓ 1 controller

The ℓ1 controller is an interesting one, since it minimizes the deviation of the controlled variables (system outputs z), in presence of unknown but bounded disturbances (system inputs w). Being defined in the time domain, this controller also allows taking into account constraints such as maximum deviations of controlled variables (z) and control action variables (u). When applied to a river or an irrigation canal this can correspond, for example, to water levels, discharges or gate openings. But, by default, like many others, this controller does not include integral effects. Several options allow forcing this effect. The paper deals with this issue and shows how a time-domain template can solve this problem, in a better way compared to other more classical options.