Receding horizon control for water resources management

Andrea Castelletti, Francesca Pianosi, Rodolfo Soncini-Sessa*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)

10 Citations (Scopus)

Abstract

Integrated water resources management (IWRM) is recognized worldwide as the reference paradigm to meet society's long-term needs for water resources while maintaining essential ecological services and economic benefits. In previous publications [A. Castelletti, R. Soncini-Sessa, A procedural approach to strengthening integration and participation in water resource planning, Environmental Modelling & Software 21(10) (2006) 1455 1470; A. Castelletti, F. Pianosi, R. Soncini-Sessa, Integration, participation and optimal control in water resources planning and management, Applied Mathematics and Computation, (2007), doi: 10.1016/j.amc.2007.09.069], the authors have already insisted on the need for a procedural approach to make the IWRM paradigm truly operational; they have emphasized the role played by dynamic optimization in rationalizing and facilitating the selection by the decision maker of a best compromise planning alternative. When planning alternatives also include management policies, as in the case of the water reservoir networks considered in this paper, the best compromise off-line policy resulting from the planning exercise has to be actually implemented in the daily management of the system. Here, again, dynamic optimization may play a central role, as it can be adopted on-line to improve the performance of the off-line policy by exploiting any new useful information available in real-time (e. g., inflow predictions, a power station being temporarily out of service, etc.). In this paper, this approach is explored through a real-world case study of a simple reservoir system. The off-line management policy computed in a previous planning process is refined on-line with a receding horizon control scheme combined with an inflow predictor. The results yield indications that the approach can provide significant advantages to cope with extreme events, particularly those occurring in unusual periods of the year. (C) 2008 Elsevier Inc. All rights reserved.

Original languageEnglish
Pages (from-to)621-631
Number of pages11
JournalApplied Mathematics and Computation
Volume204
Issue number2
DOIs
Publication statusPublished - 15 Oct 2008
EventWorkshop on New Approaches in Dynamic Optimization to Assessment of Economic and Environmental Systems - Laxenburg, Austria
Duration: 5 Dec 20067 Dec 2006

Keywords

  • Adaptive control
  • Water resources management
  • Stochastic optimal control

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