Case Gas processing – Optimization through improved control
Onshore gas processing plants in Norway have been equipped with advanced control systems, in order to obtain explicit control of product properties (impurities), while at the same time, energy consumption has decreased, and available processing capacity has increased.
Optimization by control of impurities
By specifying the product impurities, plant personnel may optimize the production from different perspectives:
- High setpoint values, close to the customer specified maximum levels, decreases the energy consumption and thus the need of steam to the reboilers. This implies energy optimization through “minimum energy consumption” for the specific distillation column
- For NGL products with significant price difference, the separation should be done in such a way that the flow of the most valuable product is maximized. This implies higher impurity for the high value component and lower impurity for the low value component. This strategy represents a simplified kind of economic optimization, not considering the energy costs.
- Only average values (on storage tank) are critical, thus higher impurities may be allowed (outside spec) for shorter periods in order to increase capacity during transients (e.g. temporary feed increase)
Optionally, a detailed economic optimizer, handling feed compositions, product prices, flow routing and energy consumption, could be implemented on the top of the different MPC applications. The different MPCs will thus constitute a required control layer in order to achieve the economical optimum.
Requirements for the process control to handle feed changes and allow for flexible flow routing between trains of columns, have made implementation of advanced control critical in order to operate the plant without increasing the control room resources.
The implementation of a number of MPC applications at Statoil’s gas processing facilities has been carried out through a tight cooperation between personnel in Statoil and Cybernetica. Cybernetica has been involved because of the company’s experience in the development and implementation of MPC. The applications are implemented in “SEPTIC” – Statoil’s in-house tool for MPC. A total number of approximately 25 MPC applications were implemented at two different sites, and Cybernetica-personnel were involved in all of them. The activities lasted for about 3-5 years, including initial application maintenance and hand-over to local personnel. A detailed study of the different PID controller loops was performed ahead of the implementations, covering re-tuning of more than 100 PID-controllers.
None of the basic PI(D) controller loops in the plant are removed. The MPC applications therefore regards the setpoints of the basic controllers as it’s free or manipulated variables. For a pure two-point distillation column, this typically means
- the septoint of reflux flow controller (FIC)
- the setpoint of column bottom temperature controller (TIC)
Setpoints for level controllers and pressure controllers are used as manipulated variables in a few cases. If not used, the values are typically given from design requirements.
The main disturbances of the separation units are the changes in feed flow and feed composition. These variables are not manipulated, but the MPC application detects the variations and compensate for the effects by changing the manipulated variables.
Dynamic models have therefore been established from each of the input variables, both disturbances and manipulated variables, to each of the controlled variables. The controlled variables are typically
- Light (top) product impurity, that means concentration of heavy component
- Heavy (bottom) product impurity, that means concentration of light component
- Differential pressure across the column
The impurities are typically estimated by soft sensors, based on column temperatures and pressure, and updated from gas chromatographs when new sample analysis are available. The differential pressure is used as an indication of column load, and will typically only be controlled below a certain maximum value, in order to prevent column flooding.00