Short Communication - (2021) Volume 0, Issue 0
Natural gas plant operations contribute hugely to the economies of many developed nations that depend on hydrocarbon resources. The plant operation is usually subjected to continuous variations in upstream conditions, such as flow rate, composition, temperature and pressure, which propagate through the plant and affect its stable operations. As a result, decision making for optimal operating conditions of an in-operation plant is a complex problem and it is exacerbated with the changing product specifications and variations in energy supplies. This work presents a new solution method to the problem, which is based on chance constrained optimization. A deterministic model is initially developed from process simulation using Aspen HYSYS and later converted to a chance constrained model. The probabilistic model is then relaxed to its equivalent deterministic form and solved for optimum solution using GAMS. The optimum solution is determined probabilistically using chance constraints that are held at a user-defined confidence level. Optimal solution is represented graphically as a trade-off between reliability of holding the process constraints and profitability of the plant. Two case studies are presented to demonstrate the new method. Optimization results show that uncertainty of plant parameters significantly affect the economic performance of the plant operation. The solution approach developed in this work is able to increase the reliability of maintaining the profit by more than 95% confidence level. As a result, the risk of constraints violation is reduced from more than 50% using the typical deterministic optimization to less than 5% with the developed chance constrained optimization model. In addition, the results from this study indicate that the variation of material flow from the plant inlet has greater impact by more than 86% on profit change compared to variation from the plant outlet, which is less than 2%. Sensitivity analysis results show on how to reduce the effect of N2, CO2 and C5+ by holding the corresponding constraint at a certain confidence level. The developed solution method can aid as guidelines to flexible plant operation decision making for the in-operating plant by satisfying all the process constraints at certain confidence level.
Mesfin Getu is currently working as Assistant Professor & Programme Director of Studies (PDoS) for Chemical Engineering at Heriot-Watt University, Dubai Campus. He obtained all his BSc, MSc and PhD degrees in Chemical Engineering. Before he joined Heriot-Watt University, he has worked as a Postdoc Fellow at Yeungnam University (South Korea) and as Senior Lecturer at Curtin University (Malaysia). He has won several awards both at the local and international levels. He has got award from IChemE (Institution of Chemical Engineers) for Research Innovation & Excellence and HoneyWell Design Challenge Competitions. He is Associate member of the institution of chemical engineers (AMIChemE) and member of the American institute of chemical engineers (MAIChE). He is also the reviewer for various chemical engineering related Journals.
Citation: Mesfin Getu ,Journal of Advanced Chemical Engineering, A Probablisitic Approach for Optimal Operation of Gas Processing Plant under Uncertain inlet-outlet Conditions. Petro Chemistry 2020, International Conference on Petro Chemical Engineering and Natural Resources, June 8-9, 2020, 08
Received: 23-Apr-2020 Published: 29-Sep-2020, DOI: 10.35248/2329-6836.21.S3-009
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