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Effective Generalized Disjunctive Programming Models for Modular Process Synthesis
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DOI：10.1021/acs.iecr.8b04600.png)
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Abstract
En 中文
We propose an optimization-based strategy to systematically evaluate trade-offs associated with modular alternatives for the multiperiod design of a chemical processing network. We give a general formulation as a Generalized Disjunctive Program (GDP) and discuss a linearizing reformulation that exploits structure common to modular design problems. By modeling the GDP in the Pyomo algebraic modeling language, we gain access to a flexible set of automatic reformulations and solution algorithms, from which the best tool may be selected to optimize a given model. We apply the design strategy to a set of illustrative case studies, including capacity expansion, bioethanol processing, and heat exchange network design. The results show that the proposed design strategy is able to solve modular design problems and provide general insights on trade-offs between investment and transportation costs in which incorporation of modular facility constructions may or may not prove to be advantageous.
Keywords:
PROCESS INTENSIFICATION
OPTIMIZATION MODELS
ALLOCATION
ALGORITHM
SYSTEMS
DESIGN
MOBILE
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