Insightful heat exchanger network retrofit design using Monte Carlo simulation

Nathan S. Lal, Martin J. Atkins, Timothy G. Walmsley, Michael R.W. Walmsley and James R. Neale

Energy, 2019, vol. 181, issue C, 1129-1141

Abstract: The aim of this paper is to use Monte Carlo simulation (MCS) to analyse the effect of stream data variation on the performance of retrofitted heat exchanger networks. MCS offers a stochastic approach to retrofit design analysis by using historical stream data to model how a retrofitted network would perform over time. The method is demonstrated with two case studies. The first is an illustrative example that showcases the features of the proposed method, while the second is a real-life case study using historical data from a section of a Kraft mill's heat exchanger network. The results show how MCS can be used as a comparison tool between exchangers and networks, differentiating between designs with similar steady-state performance, and offering insights into the reliability of the heat exchangers. For example, in the case study, the MCS results show that an estimated 62% of the time, a cold stream will exceed its target temperature under one of the retrofit proposals (which could have serious process operation and safety issues). MCS also offers another way of conducting an economic analysis which has so far tended to be less optimistic than the steady-state analysis and offers greater confidence in the profitability estimates.

Keywords: Monte Carlo simulation; Heat exchanger network; Process retrofit; Heat recovery (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S036054421931165X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:181:y:2019:i:c:p:1129-1141

DOI: 10.1016/j.energy.2019.06.042

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().