Heat Exchanger Network Synthesis with Detailed Heat Exchanger Sizing

Abstract

The increase of energy cost and usage in worldwide chemical industries leads to rising awareness for incorporating economic-efficient ways of saving energy. Heat exchanger networks (HEN) are important in process industries since they can improve energy efficiency and reduce “greenhouse” gas emissions by heat integration. The benefits can be attributed into HEN for achieving energy saving, but heat exchangers require significant capital cost at the same time and need to be allocated across an efficient network configuration for massive process streams, which leads to the HEN design becoming a complex optimization problem. Therefore, a systematic methodology for HEN synthesis is necessary to investigate these design issues for achieving a trade-off between energy and capital costs. This thesis develops a systematic optimization-based approach to achieve realistic and economic-efficient HEN synthesis with detailed heat exchanger sizing, which aims to overcome the drawbacks in existing methods associated with the application of short-cut HEN model using constant heat transfer coefficients and simplified exchanger capital cost calculation. This approach further presents how these exchanger details from the exchanger sizing can be employed to guide the HEN superstructure towards generating more economic efficient solutions, rather than a HEN with the individual unit designs. Three innovations are presented in this work. In the first innovation, a generalized disjunctive programming model for STHE sizing is proposed to improve the time-consuming design procedures and varied solution qualities caused by extensive user manipulation and fine-tuning of widely accepted commercial software. The model is formulated as a mixed-integer nonlinear programming (MINLP) problem, involving a selection of 12 technology combinations. Both global and local optimization solvers are tested. The results show the developed STHE sizing method can provide better design solutions compared with conventional design procedures. Secondly, approaches to obtain optimal HEN solutions can be based on deterministic and stochastic algorithms, but it is still challenging to tackle the large-scale HEN synthesis problems due to the complexities arisen from nonlinearities. An enhanced deterministic approach using stage-wise superstructure is also presented to support the network searching. The present model is extended to allow a flexible requirement of stream splitting for practical application. The deterministic-based solver (BARON) shows better performance by comparing the results with existing works using stochastic algorithms. Furthermore, unlike conventional methods of allocating utilities to achieve target temperatures at the end of streams, efficient utilization of waste heat in heat sources and intermediate placements of low-level hot utilities in heat sinks can dramatically improve the process energy efficiency. An enhanced stage-wise superstructure is presented to automatically optimize selections of stages covering waste heat recovery and multiple hot utilities. Grand composite curve (GCC) is adopted to implement preliminary simplifications for the superstructure, by cutting the inappropriate utilities according to the pinch method and minimum temperature driving force to eliminate redundant combinations. Finally, by integrating the presented HEN superstructure approach with heat exchanger design, a novel iterative-based decomposition approach is proposed to synthesize the HEN considering exchanger geometrical details. Fouled individual stream heat transfer coefficients and corrected total process cost are updated iteratively between the HEN superstructure and STHE design model. In each iterative procedure, exchanger geometrical details are optimized to achieve optimal thermodynamic performance for the current HEN configuration. Global optimization for heat exchangers is achieved to reduce the network investment cost and improve the unstable iteration process caused by local optimums. Consequently, the proposed approach can time-efficiently address the HEN synthesis by incorporating heat exchanger details and provide economic-efficient solutions.

Date of Award	1 Nov 2022
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Robin Smith (Co Supervisor) & Nan Zhang (Main Supervisor)