Economic Reliability-Aware MPC-LPV based on Chance-Constraints Programming for Water Networks

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Titel: Economic Reliability-Aware MPC-LPV based on Chance-Constraints Programming for Water Networks
Autoren: Karimi Pour, Fatemeh, Puig Cayuela, Vicenç, Cembrano Gennari, Gabriela
Weitere Verfasser: Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Institut de Robòtica i Informàtica Industrial, Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), European Commission, Ministerio de Economía y Competitividad (España), Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
Quelle: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Digital.CSIC. Repositorio Institucional del CSIC
instname
Consejo Superior de Investigaciones Científicas (CSIC)
Verlagsinformationen: IEEE, 2020.
Publikationsjahr: 2020
Schlagwörter: 0209 industrial biotechnology, Control predictiu, Aigua -- Abastament, Informàtica::Automàtica i control [Àrees temàtiques de la UPC], Àrees temàtiques de la UPC::Informàtica::Automàtica i control, 02 engineering and technology, Predictive control, 0101 mathematics, 01 natural sciences, Water-supply
Beschreibung: This paper proposed an economic reliabilityaware model predictive control (MPC) for the management of drinking water transport networks (DWNs) that includes a new goal to increase the system and components reliability based on a finite horizon stochastic optimization problem with joint probabilistic (chance) constraints. The proposed approach is based on a single-layer economic optimization problem with dynamic constraints. The inclusion of components and system reliability in the MPC model using an LPV modelling approach aims at maximizing the availability of the system by estimating system reliability. The solution of the optimization problem related to the MPC problem is obtained by solving a series of Quadratic Programming (QP) problem. The use of chance-constraint programming allows computing an optimal policy based on a desirable risk acceptability level and managing dynamically volume tank stocks to cope with non-stationary flow demands. Finally, the proposed approach is applied to a part of a real drinking water transport network of Barcelona for demonstrating the performance of the method.
Publikationsart: Article
Conference object
Dateibeschreibung: application/pdf
DOI: 10.23919/ecc51009.2020.9143825
DOI: 10.13039/501100011033
DOI: 10.13039/501100000780
DOI: 10.13039/501100003329
Zugangs-URL: https://upcommons.upc.edu/bitstream/2117/340030/1/0417.pdf
http://hdl.handle.net/2117/340030
http://hdl.handle.net/10261/235571
https://ieeexplore.ieee.org/document/9143825
https://dblp.uni-trier.de/db/conf/eucc/eucc2020.html#PourPC20
http://digital.csic.es/bitstream/10261/235571/1/2432-Economic-reliability-aware-MPC-LPV-based-on-chance-constraints-programming-for-water-networks..pdf
https://digital.csic.es/handle/10261/235571
https://upcommons.upc.edu/handle/2117/340030
https://upcommons.upc.edu/bitstream/2117/340030/1/0417.pdf
Rights: STM Policy #29
CC BY NC ND
Dokumentencode: edsair.doi.dedup.....40eb91b51b39e3cb7630fa844d52a07c
Datenbank: OpenAIRE