A research/development digital twin project, led by Dr. Daniel Chen in the Chemical Engineering Department, designed to establish the economic optimization and sensitivity to product price fluctuations of an entire NGL fractionation train has been accomplished using price data available from the Energy Information Administration ("EIA"). It was determined that the de-methanizer is the most profitable column and the de-ethanizer is the least profitable - in general, it is more beneficial to take the 'ethane rejection' route in operating an NGL fractionation train.
Using EIA price data from 2017 through 2021, it was found that for a NGL train with a 37,550 pounds per hour feed rate, real market NGL product price fluctuations caused profits to vary from $700 per hour to $4,000 per hour and optimization based on product price fluctuations could enhance profits by 11%. The optimization results need to be implemented with column
To date, dynamic simulations of an NGL fractionation train for tuning the de-methanizer to the de-isobutanizer have been performed with Aspen Hysys under which various controllers are digitally installed for column pressure, reboiler/condenser level, and tray temperature control. This dynamic model can be used to implement set point changes in an NGL fractionation train in response to current market pricing of NGL products.
The research team is seeking an industry partner to enable verification of the model with real world process flow and instrument diagrams, equipment sizing, and plant data from an actual NGL fractionation train.