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Water demand forecasting for the optimal operation of large-scale drinking water networks: the Barcelona case study
Sampathirao, Ajay Kumar; Grosso Pérez, Juan Manuel; Sopasakis, Pantelis; Ocampo-Martínez, Carlos; Bemporad, Alberto; Puig Cayuela, Vicenç
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control
Drinking Water Networks (DWN) are large-scale multiple-input multiple-output systems with uncertain disturbances (such as the water demand from the consumers) and involve components of linear, non-linear and switching nature. Operating, safety and quality constraints deem it important for the state and the input of such systems to be constrained into a given domain. Moreover, DWNs' operation is driven by time-varying demands and involves an considerable consumption of electric energy and the exploitation of limited water resources. Hence, the management of these networks must be carried out optimally with respect to the use of available resources and infrastructure, whilst satisfying high service levels for the drinking water supply. To accomplish this task, this paper explores various methods for demand forecasting, such as Seasonal ARIMA, BATS and Support Vector Machine, and presents a set of statistically validated time series models. These models, integrated with a Model Predictive Control (MPC) strategy addressed in this paper, allow to account for an accurate on-line forecasting and flow management of a DWN.
Peer Reviewed
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
automation
control theory
optimisation
predictive control
disturbance forecasting
large-scale systems. model predictive control
industrial processes
Classificació INSPEC::Optimisation
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/submittedVersion
info:eu-repo/semantics/conferenceObject
International Federation of Automatic Control (IFAC)
         

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