Design of Robust Total Site Heat Recovery Loops via Monte Carlo Simulation

Florian Schlosser, Ron-Hendrik Peesel, Henning Meschede, Matthias Philipp, Timothy G. Walmsley, Michael R. W. Walmsley and Martin J. Atkins
Additional contact information
Florian Schlosser: Dep. Umweltgerechte Produkte und Prozesse, Universität Kassel, Kurt-Wolters-Straße 3, 34125 Kassel, Germany
Ron-Hendrik Peesel: Dep. Umweltgerechte Produkte und Prozesse, Universität Kassel, Kurt-Wolters-Straße 3, 34125 Kassel, Germany
Henning Meschede: Dep. Umweltgerechte Produkte und Prozesse, Universität Kassel, Kurt-Wolters-Straße 3, 34125 Kassel, Germany
Matthias Philipp: Bayernwerk Natur GmbH, Carl-von-Linde-Straße 38, 85716 Unterschleißheim, Germany
Timothy G. Walmsley: Sustainable Process Integration Laboratory–SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of Technology-VUT Brno, Technická 2896/2, 616 69 Brno, Czech Republic
Michael R. W. Walmsley: Energy Research Centre, School of Engineering, University of Waikato, Private Bag 3105, Hamilton 3240, New Zealand
Martin J. Atkins: Energy Research Centre, School of Engineering, University of Waikato, Private Bag 3105, Hamilton 3240, New Zealand

Energies, 2019, vol. 12, issue 5, 1-17

Abstract: For increased total site heat integration, the optimal sizing and robust operation of a heat recovery loop (HRL) are prerequisites for economic efficiency. However, sizing based on one representative time series, not considering the variability of process streams due to their discontinuous operation, often leads to oversizing. The sensitive evaluation of the performance of an HRL by Monte Carlo (MC) simulation requires sufficient historical data and performance models. Stochastic time series are generated by distribution functions of measured data. With these inputs, one can then model and reliably assess the benefits of installing a new HRL. A key element of the HRL is a stratified heat storage tank. Validation tests of a stratified tank (ST) showed sufficient accuracy with acceptable simulation time for the variable layer height (VLH) multi-node (MN) modelling approach. The results of the MC simulation of the HRL system show only minor yield losses in terms of heat recovery rate (HRR) for smaller tanks. In this way, costs due to oversizing equipment can be reduced by better understanding the energy-capital trade-off.

Keywords: total site heat integration; heat recovery loop (HRL); heat storage; Monte Carlo (MC) simulation; data farming (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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