| Título | Stochastic model predictive control approaches applied to drinking water networks |
|---|---|
| Autores | Grosso, Juan M. , VELARDE RUEDA, PABLO ANIBAL, Ocampo-Martinez, Carlos , Maestre, Jose M. , Puig, Vicenc |
| Publicación externa | Si |
| Medio | Optim Control Appl Methods |
| Alcance | Article |
| Naturaleza | Científica |
| Cuartil JCR | 1 |
| Cuartil SJR | 1 |
| Impacto JCR | 1.614 |
| Impacto SJR | 0.825 |
| Fecha de publicacion | 01/07/2017 |
| ISI | 000405077500005 |
| DOI | 10.1002/oca.2269 |
| Abstract | Control of drinking water networks is an arduous task, given their size and the presence of uncertainty in water demand. It is necessary to impose different constraints for ensuring a reliable water supply in the most economic and safe ways. To cope with uncertainty in system disturbances due to the stochastic water demand/consumption and optimize operational costs, this paper proposes three stochastic model predictive control (MPC) approaches, namely, chance-constrained MPC, tree-based MPC, and multiple-scenario MPC. A comparative assessment of these approaches is performed when they are applied to real case studies, specifically, a sector and an aggregate version of the Barcelona drinking water network in Spain. Copyright (c) 2016 John Wiley & Sons, Ltd. |
| Palabras clave | management of water systems; model predictive control; stochastic programming; system disturbances |
| Miembros de la Universidad Loyola |