Insightful heat exchanger network retrofit design using Monte Carlo simulation

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.