PREGO
2009-2010
OBJECTIVES
The PREGO project is a Spanish-French project aimed at developing and applying predictive multi-criteria management methods for hydrographic systems to assist in decision-making during water crisis situations in the Pyrenean massif.
The objectives of the project are:
The objectives of the project are:
Modeling the flow combined with inflows and extractions for a simulation compatible with the management horizon.
Modeling crisis situations: resource growth or shortage.
Data consistency and diagnosis of the hydraulic network state.
Management of large networks with managed and unmanaged hydrographic subsystems.
Impact of a crisis situation in a subsystem on the overall network management.
Crisis management and decision support.
Application to the hydrographic networks of the Pyrenees.
SUMMARY
Improving water management in the Pyrenean basin through research development and its transfer has a real economic, social, and environmental impact. For this reason, it is crucial to propose a set of methods that ensure predictive management of water resources to better guarantee the satisfaction of growing human activity demands. Water demand in the Pyrenees is partly linked to agricultural irrigation and partly to river replenishment to dilute tributaries, maintain aquatic environments in good ecological condition, as required by the European Water Framework Directive (WFD), and provide drinking water. The sensor networks and remotely controlled actuators enable real-time monitoring of flows, levels, water quality, etc., thus allowing remote control of intake points, valves, either in a centralized or distributed manner.
This project will focus on multi-level resource management, incorporating decision-making aspects for short- and medium-term adaptations to fluctuations in supply and demand. However, for management to be predictive, it must involve knowledge of resource status and satisfy demand according to established consumption contracts and forecasts of extractions and inflows. Anticipation and reaction must be combined to ensure proper water management. Control of these hydrographic resources requires developing dynamic models that represent the behavior of open-channel hydraulic systems such as rivers and canals, in the presence of inflows due to rainfall and consumption from industrial, agricultural, or drinking water uses. Through simulation tools, it is possible to visualize the impact of a management model. Consequently, management scenarios can be defined in advance to establish action plans, mainly in crisis situations such as resource depletion or sudden, localized, heavy rainfall events affecting a part of the basin. For this purpose, different levels of crisis can be considered.
This project will focus on multi-level resource management, incorporating decision-making aspects for short- and medium-term adaptations to fluctuations in supply and demand. However, for management to be predictive, it must involve knowledge of resource status and satisfy demand according to established consumption contracts and forecasts of extractions and inflows. Anticipation and reaction must be combined to ensure proper water management. Control of these hydrographic resources requires developing dynamic models that represent the behavior of open-channel hydraulic systems such as rivers and canals, in the presence of inflows due to rainfall and consumption from industrial, agricultural, or drinking water uses. Through simulation tools, it is possible to visualize the impact of a management model. Consequently, management scenarios can be defined in advance to establish action plans, mainly in crisis situations such as resource depletion or sudden, localized, heavy rainfall events affecting a part of the basin. For this purpose, different levels of crisis can be considered.
Conceptual diagram of the PREGO project
Most notable publications
E. Duviella, V. Puig, P. Charbonnaud, J. Quevedo, F.J. Carrillo, T. Escobet (2010). Supervised Gain-scheduling Multi-model vs LPV IMC of Open-Channel Systems for Large Operating Conditions. Journal of Irrigation and Drainage Engineering. <doi: 10.1061/(ASCE)IR.1943-4774.0000219>Puig, V., Ocamp, C (2010). Piece-wise linear functions-based model predictive control of large-scale sewage systems. Control Theory & Applications, IET , vol.4, no.9, pp.1581-1593. <doi: 10.1049/iet-cta.2009.0206>
Ocampo-Martínez, C., Fambrini, V., Barcelli, D., Puig, V. (2010). Model Predictive Control of Drinking Water Networks: A Hierarchical and Decentralized Approach. ACC 2010 American Control Conference, Baltimore, USA, pp.3951-3956. URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5530643&isnumber=5530425
Javalera, V., Morcego, B., Puig, V. (2010). Negotiation and Learning in Distributed MPC of Large Scale Systems: the MPC Architecture. ACC 2010 American Control Conference. Baltimore, USA, pp. 3168-3173. URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5530986&isnumber=5530425
Javalera, V., Morcego, B., Puig, V. (2010). A Multi-Agent MPC Architecture for Distributed Large Scale Systems. ICAART International Conf. on Agents and Artificial Intelligence. Valencia. Spain.
Barcelli, D., Ocampo-Martínez, C., Puig, V. Bemporad, A. (2010). Model Predictive Control of Drinking Water Networks: A Hierarchical and Decentralized Approach. American Control Conference (ACC), pp.3951-3956. URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5530643&isnumber=5530425.
Javalera, V., Morcego, B., Puig, V. (2010). Distributed MPC for large scale systems using agent-based reinforcement learning. IFAC symposium on Large Scale Complex Systems Theory and Applications, V. 9, Lille, France. <10.3182/20100712-3-FR-2020.00097>
R. Pérez, V. Puig, J. Pascual, J. Quevedo, E. Landeros, A. Peralta (2010). Leakage isolation using pressure sensitivity analysis in water distribution networks: Application to the Barcelona case study. IFAC symposium on Large Scale Complex Systems Theory and Application, Lille, France.
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