4.6 Article

MINLP model and two-stage algorithm for the simultaneous synthesis of heat exchanger networks, utility systems and heat recovery cycles

Journal

COMPUTERS & CHEMICAL ENGINEERING
Volume 106, Issue -, Pages 663-689

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2017.01.043

Keywords

HEN synthesis; Heat integration; Steam cycles; Utility synthesis; MINLP; MILP

Funding

  1. Swiss National Science Foundation (SNSF) [IZK0Z2_157270]
  2. Swiss Competence Center on Energy Research, Efficiency in Industrial Processes (SCCER-EIP) from the Swiss Confederation Commission for Technology and Innovation
  3. Swiss National Science Foundation (SNF) [IZK0Z2_157270] Funding Source: Swiss National Science Foundation (SNF)

Ask authors/readers for more resources

This work proposes a novel approach for the simultaneous synthesis of Heat Exchanger Networks (HEN) and Utility Systems of chemical processes and energy systems. Given a set of hot and cold process streams and a set of available utility systems, the method determines the optimal selection, arrangement and design of utility systems and the heat exchanger network aiming to rigorously consider the trade-off between efficiency and capital costs. The mathematical formulation uses the SYNHEAT superstructure for the HEN, and ad hoc superstructures and nonlinear models to represent the utility systems. The challenging nonconvex MINLP is solved with a two-stage algorithm. A sequential synthesis algorithm is specifically developed to generate a good starting solution. The algorithm is tested on a literature test problem and two industrial problems, the optimization of the Heat Recovery Steam Cycle of a Natural Gas Combined Cycle and the heat recovery system of an Integrated Gasification Combined Cycle. (C) 2017 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available