Grosso, Juan M. , VELARDE RUEDA, PABLO ANIBAL, Ocampo-Martinez, Carlos , Maestre, Jose M. , Puig, Vicenc
Si
Optim Control Appl Methods
Article
Científica
1.614
0.825
01/07/2017
000405077500005
2-s2.0-84983001937
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.
management of water systems; model predictive control; stochastic programming; system disturbances