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

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

Článek WoS

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.

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.

Data farming; Heat recovery loop (HRL; )Heat storage; Monte Carlo (MC) simulation; Total site heat integration; Digital storage; Distribution functions; Economic and social effects; Intelligent systems; Stochastic models; Stochastic systems; Tanks (containers); Time series; Waste heat; Discontinuous operation; Economic efficiency; Heat integration; Heat storage tanks; Performance Model; Robust operation; Stochastic time series; Monte Carlo methods

Data farming; Heat recovery loop (HRL; )Heat storage; Monte Carlo (MC) simulation; Total site heat integration; Digital storage; Distribution functions; Economic and social effects; Intelligent systems; Stochastic models; Stochastic systems; Tanks (containers); Time series; Waste heat; Discontinuous operation; Economic efficiency; Heat integration; Heat storage tanks; Performance Model; Robust operation; Stochastic time series; Monte Carlo methods

Schlosser, F.; Peesel, R.H.; Meschede, H.; Philipp, M.; Walmsley, T.G.; Walmsley, M.R.W.; Atkins, M.J.

2020

01.03.2019

MDPI AG

1996-1073

Energies

5

12

Švýcarská konfederace

930

940

10

https://www.mdpi.com/1996-1073/12/5/930