An MPEC formulation for dynamic optimization of distillation operations
We consider the dynamic optimization of chemical processes with changes in the number of equilibrium phases. Recent work has shown that transitions in the number of phases can be modeled as a mathematical program with equilibrium constraints (MPEC). This study generalizes the MPEC to consider dynami...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2004 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/127014 |
| Acceso en línea: | http://hdl.handle.net/11336/127014 |
| Access Level: | acceso abierto |
| Palabra clave: | BARRIER METHODS COMPLEMENTARITY CONDITIONS DISTILLATION DYNAMIC OPTIMIZATION NONLINEAR PROGRAMMING https://purl.org/becyt/ford/2.4 https://purl.org/becyt/ford/2 |
| Sumario: | We consider the dynamic optimization of chemical processes with changes in the number of equilibrium phases. Recent work has shown that transitions in the number of phases can be modeled as a mathematical program with equilibrium constraints (MPEC). This study generalizes the MPEC to consider dynamic characteristics. In particular, we describe a simultaneous discretization and solution strategy for dynamic optimization problems with complementarity constraints. These discretized problems are then solved with IPOPT-C, a recently developed barrier method for MPEC problems. Our approach is applied to two distillation examples. In the first, we consider the optimal startup of a binary batch distillation problem. In the second, we consider the dynamic operation of a cryogenic column for the separation of natural gas liquids. Both cases demonstrate the effectiveness of the approach on large scale MPEC problems. |
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