relation: http://eprints.imtlucca.it/2326/
title: Water demand forecasting for the optimal operation of large-scale drinking water networks: the Barcelona case study
creator: Sampathirao, Ajay Kumar
creator: Grosso Pérez, Juan Manuel
creator: Sopasakis, Pantelis
creator: Ocampo-Martinez, Carlos
creator: Bemporad, Alberto
creator: Puig, Vicenç
subject: QA75 Electronic computers. Computer science
description: 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.
publisher: IFAC
date: 2014-08
type: Book Section
type: PeerReviewed
format: application/pdf
language: en
identifier: http://eprints.imtlucca.it/2326/1/Sopasakis_19IFAC14.pdf
identifier:   Sampathirao, Ajay Kumar and Grosso Pérez, Juan Manuel and Sopasakis, Pantelis and Ocampo-Martinez, Carlos and Bemporad, Alberto and Puig, Vicenç  Water demand forecasting for the optimal operation of large-scale drinking water networks: the Barcelona case study.   In:  Proceedings of the 19th IFAC World Congress.   IFAC, pp. 10457-10462.  ISBN 978-3-902823-62-5    (Unpublished)   (2014)  
relation: http://www.ifac-papersonline.net/Detailed/68585.html
relation: 10.3182/20140824-6-ZA-1003.01343