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Título : | MILP for optimizing water allocation and reservoir location: a case study for the Machángara river basin, Ecuador |
Autor: | Veintimilla Reyes, Jaime Eduardo De Meyer, Annelies Cattryss, Dirk Tacuri Espinoza, Victor Eduardo Vanegas Peralta, Pablo Fernando Cisneros Espinosa, Felipe Eduardo francisco Van Orshoven, Jos |
Palabras clave : | MILP LP Network flow optimization problem (NFOP) Water allocation Reservoir optimization Machángara |
Área de conocimiento FRASCATI amplio: | 2. Ingeniería y Tecnología |
Área de conocimiento FRASCATI detallado: | 2.11.2 Otras Ingenierias y Tecnologías |
Área de conocimiento FRASCATI específico: | 2.11 Otras Ingenierias y Tecnologías |
Área de conocimiento UNESCO amplio: | 06 - Información y Comunicación (TIC) |
ÁArea de conocimiento UNESCO detallado: | 0613 - Software y Desarrollo y Análisis de Aplicativos |
Área de conocimiento UNESCO específico: | 061 - Información y Comunicación (TIC) |
Fecha de publicación : | 2019 |
Volumen: | Volumen 11, número 5 |
Fuente: | Water |
metadata.dc.identifier.doi: | https://doi.org/10.3390/w11051011 |
Tipo: | ARTÍCULO |
Abstract: | The allocation of water flowing through a river-with-reservoirs system to optimally meet spatially distributed and temporally variable demands can be conceived as a network flow optimization (NFO) problem and addressed by linear programming (LP). In this paper, we present an extension of the strategic NFO-LP model of our previous model to a mixed integer linear programming (MILP) model to simultaneously optimize the allocation of water and the location of one or more new reservoirs; the objective function to minimize only includes two components (floods and water demand), whereas the extended LP-model described in this paper, establishes boundaries for each node (reservoir and river segments) and can be considered closer to the reality. In the MILP model, each node is called a “candidate reservoir” and corresponds to a binary variable (zero or one) within the model with a predefined capacity. The applicability of the MILP model is illustrated for the Machángara river basin in the Ecuadorian Andes. The MILP shows that for this basin the water-energy-food nexus can be mitigated by adding one or more reservoirs. |
Resumen : | The allocation of water flowing through a river-with-reservoirs system to optimally meet spatially distributed and temporally variable demands can be conceived as a network flow optimization (NFO) problem and addressed by linear programming (LP). In this paper, we present an extension of the strategic NFO-LP model of our previous model to a mixed integer linear programming (MILP) model to simultaneously optimize the allocation of water and the location of one or more new reservoirs; the objective function to minimize only includes two components (floods and water demand), whereas the extended LP-model described in this paper, establishes boundaries for each node (reservoir and river segments) and can be considered closer to the reality. In the MILP model, each node is called a “candidate reservoir” and corresponds to a binary variable (zero or one) within the model with a predefined capacity. The applicability of the MILP model is illustrated for the Machángara river basin in the Ecuadorian Andes. The MILP shows that for this basin the water-energy-food nexus can be mitigated by adding one or more reservoirs. |
URI : | https://www.mdpi.com/2073-4441/11/5/1011 |
URI Fuente: | https://www.mdpi.com/journal/water |
ISSN : | 2073-4441 |
Aparece en las colecciones: | Artículos
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