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Simultaneous Process and Economic Uncertainty Analysis

Computational Methods

Use modeling software to quickly evaluate the impact of process uncertainties on the economics of chemical processes during the development stage.

In the early stages of technology development, process simulators such as Aspen Plus and Aspen HYSYS enable engineers to quickly evaluate new processes. However, at that stage, the process simulation models typically consist of process and economic variables with high uncertainty. Therefore, it is important to analyze the effect of uncertainties on the economic value metrics that are used in the decision-making process. Sensitivity analysis, a common practice to investigate the effect of these uncertainties, is usually performed by changing each variable one at a time. However, it does not account for the effect of combined uncertainties associated with multiple process variables. Monte Carlo simulation — with the defined probabilistic distributions of the input or uncertain variables — calculates the probabilistic distribution for the output process variables, which can be used to determine the probability of occurrence of a specific event of interest.

Monte Carlo simulations that are performed in an isolated manner on either the process or economics side alone may not cover the true effect of all the uncertainties on the critical value metrics such as net present value (NPV). Therefore, coupling process and economic uncertainties is essential to understand the combined effect of uncertainties. The uncertainties associated with the process variables, especially if those processes are modeled in a process simulator, are not included in this analysis due to the limitation of the current methodology. This article demonstrates an approach to uncertainty analysis that includes process variables in addition to economic variables...

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