Publication

Water demand forecasting for the optimal operation of large-scale drinking water networks: The Barcelona case study

Conference Article

Conference

IFAC World Congress (IFAC)

Edition

19th

Pages

10457-10462

Doc link

http://dx.doi.org/10.3182/20140824-6-ZA-1003.01343

File

Download the digital copy of the doc pdf document

Abstract

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.

Categories

automation, control theory, optimisation, predictive control.

Author keywords

disturbance forecasting, large-scale systems. model predictive control, industrial processes

Scientific reference

A.K. Sampathirao, J.M. Grosso, P. Sopasakis, C. Ocampo-Martínez, A. Bemporad and V. Puig. Water demand forecasting for the optimal operation of large-scale drinking water networks: The Barcelona case study, 19th IFAC World Congress, 2014, Cape Town, South Africa, pp. 10457-10462.