For those attending the Emerson Exchange with distillation processes, you don’t want to miss Emerson’s Lou Heavner‘s presentation, Advanced Distillation – 102. Lou is an advanced control consultant, whom you may recall from earlier posts. He’ll be presenting Wed, 9/30 at 4:15pm in the Sun 4 room and again Thurs, 10/1 at 9:00am in the Captiva 1 room.
Lou’s preference is to have each session be an open, interactive discussion on distillation control challenges and solution approaches. He does have a presentation and will talk if that is what the session attendees would prefer, but he’s hopeful an interactive discussion will blossom. I’ve gleaned some highlights from the presentation.
This is a picture of a traditional binary distillation column. The feed may be vapor, liquid, or a mixture, but is most commonly a liquid. Its composition is usually variable. Liquid in the bottom of the column is boiled up through the column and vapor leaving the top is condensed and returned as reflux. The product flows must equal the feed flow or the process won’t operate very long. So, the liquid level in the bottom of the column and the liquid level in the reflux accumulator are controlled by manipulating product flows or sometimes by manipulating heat to the reboiler or reflux to the column.
Usually, composition is inferred key from temperatures in the column and controlled by manipulating heat to the reboiler and reflux flow to the column. Pressure can be controlled by venting non-condensibles (if they are present) or by controlling the amount of condensing in the column overhead.
Feed is usually not available for control, but may be in some cases. When it is available, it can be a good choice for optimization–maximizing throughput. In some cases, online analyzers are available and if they are, they may be used for control or simply monitored.
Lou stresses the fact that you can’t control something that you can’t measure. Online analyzers or product purity measurements are one of the key requirements for good distillation control. If there is not an appropriate online analyzer, then some kind of inferential measurement will be required. Other measurements such as flooding (a column operating constraint) and reflux ratio can be used to track performance.
Interaction is one of the defining challenges of distillation control. Interestingly, there are many ways to pair controlled and manipulated variables. Some will work well in one column and poorly in another. The whole study of relative-gain array (RGA) analysis has been developed to understand the best way to pair control and manipulated variables. This is largely dependent on factors like product purity specs, feed composition, number of theoretical stages in the column and typical reflux ratio.
Another source of interaction outside of many columns is thermal integration. It is common for the hot product to be cooled against the feed to provide some preheat and efficiency to the column. Variability in the bottom product temperature or flow rate will be recycled back into the column through the feed. Sometimes a heat pump arrangement is used to boil the bottoms against the overhead vapors, which have been compressed. This configuration is rarely seen and only practical when the overhead and bottom products have similar boiling points and non-condensables are not present.
Another factor that makes distillation control difficult is the actual process dynamics such as long time delays associated with the time it takes for liquid reflux to cascade all of the way down to the bottom of the tower. This is more problematic when one considers that vapors will rise much more quickly up the tower. The controls need to respond to both of these kinds of dynamic responses.
When looking at the distillation process, it’s a classic multi-variable process with controlled and manipulated variables. You can include the material balance loops (i.e. the level control loops) in the model predictive control (MPC) strategy. The levels would be the control (or constraint) variables and the product flows would be the manipulated variables. There are extra, manipulated variables, so an opportunity exists to include optimization. There may also be additional constraints (e.g. flooding or valve positions) and measured disturbances (e.g. reflux temperature and feed temperature).
Lou goes on to describe interaction and the relative gain array analysis process to identify the best pairings to minimize the effect of loop interaction and simplifying the matrices. He also covers pressure compensated temperature pros and cons, multi-component distillation, level control, azeotropes, and batch distillation.
If you’ve been battling distillation issues in meeting quality specs, energy usage, yield, and/or capacity, bring these to one of the two sessions and see what thoughts Lou and fellow attendees have to offer. It will hopefully be worth your while!