Multi-objective optimization of ammonia and methanol production processes considering uncertain feedstock compositions of shale/natural gas

Abstract

This paper presents a multi-objective optimization strategy for monetizing shale/natural gas to two important products: ammonia and methanol. This study considers the uncertainty associated with the composition of the feed shale/natural gas stream. The decision variables are the feed flow and the relative allocation of the feedstock to each process. Economic and environmental objectives are used in optimization. The economic objective is to maximize the net profit while considering revenue and production costs. The environmental objective is to minimize total annual CO2 emissions associated with providing the process with the required heat and power for the reformer and the compressors, respectively. Process simulation is carried out using Aspen HYSYS. The improved multi-objective differential evolution algorithm (I-MODE) is used for the optimization strategy. A random generator routine is developed for the creation of uncertain parameter values. The programs are linked through Visual Basic for Applications as a medium to exchange data. After applying the optimization strategy, the results showed an improvement in the objective functions, where the decision-maker can choose the point in a Pareto front according to the specific tradeoff of the targeted objectives. The results offer alternatives with an increase in the net benefit of up to 26.8% with only an increase in emissions of 4.5%.