Data Reconciliation and Gross Error Detection of a Refinery Process
Client: Research Institute of Petroleum Industry
Director project: Dr. Babak Tavassoli
Project type: Simulation study
Project collaborator: K.N. Tossi University of Technology (KNTU)
Summary of project:
This project was a part of a larger collaborative research on real-time optimization (RTO) of a Hydrodesulphurization (HDS) plant. An RTO system optimized the plant performance by adjusting the setpoints of the closed loop controller in real-time, i.e. during the operation of the plant. For this purpose, it is required to provide high-quality data for the online model-based optimization. A way of improving the measurement quality is a correction of the measurement errors based on the available physical model of the plant. This process is known as model-based data reconciliation. Additionally, the plant model can be used to detect gross errors (large errors due to measurement failures).