Refinery Network Integration and Coordination

The use of mathematical programming models on an enterprise-wide scale to address strategic decisions considering various process integration alternatives yields substantial benefits. These benefits not only materialize in terms of economic considerations, but also in terms of process flexibility and improvements in the understanding of the process interactions and systems limitations. 

In this chapter, we tackle the integration design and coordination of a multisite refinery network. The main feature of the chapter is the development of a simultaneous analysis strategy for process network integration through a mixed-integer linear program (MILP). The performance of the proposed model in this chapter is tested on several industrial-scale examples to illustrate the economic potential and trade-offs involved in the optimization of the network. 

Grossmann and Park (2000) explained a classification of chemical process networks and characterized them as either dedicated or flexible processes. Dedicated processes operate at one mode and for high volume products whereas flexible processes operate at different modes and produce different products at different times. In the formulation introduced in this chapter, we account for different 

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