Modeling and economic optimization of an industrial site for natural gas processing: A nonlinear optimization approach

Abstract

In this work an integrated simulation-optimization model to determine the optimal economic operating point of an industrial site for natural gas processing with multiple process units and feedstock. Natural gas industrial facilities have the intrinsic characteristic of dealing with dynamic scenarios, with no control over raw inlet gas, which might lead the plant to suboptimal conditions. In this context, an integrated simulation-optimization framework was proposed, using Aspen HYSYS for process simulation, Python for optimization and Microsoft Excel as data transfer interface. Process model comprises three slug catchers, five gas processing units, three liquid fractionating units, compression systems, auxiliary equipment and gas treating units. The optimization problem was formulated based on the maximum business profit, incorporating, as penalty functions, inequality constraints: product specifications, logistic bottlenecks and plant physical limits. Optimization model was validated against actual data from an industrial facility responsible for processing over one quarter of all natural gas used in Brazil. The nonlinear programming was successfully executed using Particle Swarm Optimization method in series with Nelder-Mead flexible polyhedron for ten normalized decision variables indicating a potential increase of 7.3 % in variable profit, as well as the existence of local minima in the optimization space.

Keywords

• Enterprise-wide optimization
• Natural gas
• NLP
• Process simulation