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Insightful heat exchanger network retrofit design using Monte Carlo simulation

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

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.

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  • Lal, Nathan S. & Atkins, Martin J. & Walmsley, Timothy G. & Walmsley, Michael R.W. & Neale, James R., 2019. "Insightful heat exchanger network retrofit design using Monte Carlo simulation," Energy, Elsevier, vol. 181(C), pages 1129-1141.
  • Handle: RePEc:eee:energy:v:181:y:2019:i:c:p:1129-1141
    DOI: 10.1016/j.energy.2019.06.042
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    References listed on IDEAS

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    Cited by:

    1. Christian Langner & Elin Svensson & Simon Harvey, 2020. "A Framework for Flexible and Cost-Efficient Retrofit Measures of Heat Exchanger Networks," Energies, MDPI, vol. 13(6), pages 1-24, March.
    2. Klemeš, Jiří Jaromír & Wang, Qiu-Wang & Varbanov, Petar Sabev & Zeng, Min & Chin, Hon Huin & Lal, Nathan Sanjay & Li, Nian-Qi & Wang, Bohong & Wang, Xue-Chao & Walmsley, Timothy Gordon, 2020. "Heat transfer enhancement, intensification and optimisation in heat exchanger network retrofit and operation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    3. Hafizan, Ainur Munirah & Wan Alwi, Sharifah Rafidah & Manan, Zainuddin Abd & Klemeš, Jiří Jaromír & Abd Hamid, Mohd Kamaruddin, 2020. "Design of optimal heat exchanger network with fluctuation probability using break-even analysis," Energy, Elsevier, vol. 212(C).
    4. Walden, Jasper V.M. & Wellig, Beat & Stathopoulos, Panagiotis, 2023. "Heat pump integration in non-continuous industrial processes by Dynamic Pinch Analysis Targeting," Applied Energy, Elsevier, vol. 352(C).
    5. Zhou, Na & Wu, Qiaosheng & Hu, Xiangping & Zhu, Yongguang & Su, Hui & Xue, Shuangjiao, 2020. "Synthesized indicator for evaluating security of strategic minerals in China: A case study of lithium," Resources Policy, Elsevier, vol. 69(C).
    6. Zhang, Di & Lv, Donghui & Yin, Changfang & Liu, Guilian, 2020. "Combined pinch and mathematical programming method for coupling integration of reactor and threshold heat exchanger network," Energy, Elsevier, vol. 205(C).

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