Integrated synthesis and control of heat exchanger networks with dynamic flexibility consideration

Abstract

• Dynamic flexible aspect is taken into account in early integration stage. • A sequential iterative algorithm for the problem solution is devised. • Stream matches, heat transfer areas and bypass fractions are optimized. • Results indicate considerable cost (−14.95%) and control performances (+61.83%). • Major advantages found for case studies with multiple disturbances. Flexible synthesis and control which can be both used to reduce the influences of disturbances on heat exchanger networks are often considered as two separate issues assisting network development at different stages. A proper integration of these separate yet connected tasks carries the promise of achieving superior designs. Currently, the study of integration of heat exchanger networks is still towards a sequential procedure consisting of initial flexible synthesis based on steady-state economic calculations followed by a controller. To overcome this challenge, based on the stage-wise superstructure, an optimization framework in this work is presented to address dynamic flexible synthesis and advanced control simultaneously for maximizing performance in face of disturbances. The framework is based on a sequential iterative procedure that decomposes the overall problem into two stages. The first stage is performed by the dynamic flexibility analysis where the design variables are chosen. In the second stage, the optimization variables are adjusted during the discrete time intervals on the realizations of the control actions and the variation ranges of outlet stream temperatures. The sequential iterative is to map the temperature regulations to the network configuration retrofits. The application to two case studies indicates that the proposed framework returns solutions which are considerably better all in terms of dynamic flexibility, economics and control performance than those published in literature. Compared to previous literature studies, the optimized solutions feature a total annual cost reduction up to 14.95%, a decrease in control action up to 48.58% and an increase in control performance up to 61.83%. Moreover, the application to two case studies indicates that allows solving a real-world problem with up to 26 hot streams and 29 cold streams (leading to models with a size of 523 binary variables and 1655 equations).