Combining short-term and long-term reservoir operation using infinite horizon model predictive control
Raso, L. | Malaterre, Pierre-Olivier | Delft University of Technology (TU Delft) | Gestion de l'Eau, Acteurs, Usages (UMR G-EAU) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)
[Departement_IRSTEA]Eaux [TR1_IRSTEA]GEUSI
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Показать больше [+] Меньше [-]Английский. Model predictive control (MPC) can be employed for optimal operation of adjustable hydraulic structures. MPC selects the control to be applied to the system by solving an optimization problem over a finite horizon in real-time. The horizon finiteness is both the reason for MPC's success and its main limitation. MPC has in fact been successfully employed for short-term reservoir management. Short-term reservoir management deals effectively with fast processes, such as flood, but it is not capable of looking sufficiently ahead to handle long-term issues, such as drought. This study proposes an infinite horizon MPC solution that deals with both short and long-term objectives, tailored for reservoir management. In the proposed solution, the control signal is structured by the use of basis functions. Basis functions reduce the optimization argument to a small number of variables, making the control problem solvable in a reasonable time. The solution is tested for the operational management of Manantali reservoir, in the Senegal River. The long-term horizon offered by infinite horizon MPC is necessary to deal with the strongly seasonal climate of the region for both flood and drought prevention.
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