(84e) Improve Column Performance, Operate Closer to the Hydraulic Limit without Flooding

The Flooding Predictor? is a patented advanced control technology that has been proven in research at the Separations Research Program, University of Texas at Austin, to increase distillation column production by over 6%. The research was conducted under a U. S. Department of Energy Cooperative Agreement awarded to George Dzyacky of 2ndpoint, LLC. The technology works by detecting the incipient flood point and controlling the column much closer to its actual hydraulic limit than current technologies. These benefits are derived through the use of conventional instrumentation, meaning no additional refining infrastructure is required.

Refiners often push the operating severity of distillation columns, either to maximize throughput or to improve separation. Attempting to achieve such operating objectives is a tricky undertaking that often results in flooding. Operators and advanced control strategies alike rely on the conventional use of delta-pressure instrumentation to approximate the column's approach to flood. But column delta-pressure is more an inference of the column's approach to flood than it is an actual measurement of it. As a consequence, delta pressure limits are established conservatively in order to operate in a regime where the column is never expected to flood. But there is much ?left on the table? when operating in such a regime ? that is, the capacity difference between controlling the column to an upper delta-pressure limit and controlling it to the actual hydraulic limit. The Flooding Predictor?, an innovative, pattern recognition technology, controls columns at their actual hydraulic limit.

Flooding in distillation columns occurs when the liquid/vapor traffic inside the tower is sufficient to inhibit the column from making the desired separation. The two primary types of flooding in tray columns are jet flooding and downcomer flooding, each with its own tendencies. The Flooding Predictor? is capable of identifying these different flooding mechanisms. The flood-predictive capabilities of the technology have also been validated on packed columns.

The Flooding Predictor? operates on the principle that between five to sixty minutes in advance of a flooding event, certain column variables experience an oscillation, a pre-flood pattern. The pattern recognition system of the Flooding Predictor? utilizes the mathematical first derivative of certain column variables to identify the column's pre-flood pattern(s). This pattern is a very brief, highly repeatable, simultaneous movement among the derivative values of certain column variables. While all column variables experience negligible random noise generated from the natural frequency of the process, subtle pre-flood patterns are revealed among sub-sets of the derivative values of column variables as the column approaches its hydraulic limit.

The sub-set of column variables that comprise the pre-flood pattern is identified empirically through the analysis component of the Flooding Predictor?. Once the pre-flood patterns are identified, the automation component of the Flooding Predictor? is implemented on the plant's distributed control systems (DCS), thus automating control of the column at its hydraulic limit.