Benefits of High-Fidelity Dynamic Simulation

The use of high-fidelity dynamic simulation (HFDS) offers numerous benefits throughout the process lifecycle. The primary areas of benefit include better equipment sizing and selection, optimum control design, reduced errors, cost and time savings, and improved safety and training. Process and control design may benefit from HFDS. Process equipment may be sized and selected to meet not only capacity and cost but also transient requirements. For example, a high-fidelity control valve model may help size and select the valve and avoid problems such as oversizing and poor dynamic performance. A high-fidelity control valve model is often critical in tuning flow or pressure controllers in the simulation system and then applying the results directly to its real system. HFDS is important in developing and evaluating advanced process controls (APCs) at design stage to avoid poor-performing APCs in an actual plant. Tuning PID and APC controllers on high-fidelity dynamic simulation prior to commissioning the system saves time and cost. HFDS simulates behaviors and performance not only under normal conditions but also during startup, shutdown and abnormal conditions. Therefore it can be used to check out and verify that individual equipment and the overall system will perform as designed, thereby minimizing costly design errors. Designers can use the simulation to verify process control strategy and operation procedures during abnormal events such as equipment malfunctions and process disturbances. It is a powerful tool for training operators to handle various normal and abnormal operating conditions. Distributed with permission of author(s) by ISA 2011 Presented at ISA Automation Week 2011; http://www.isa.org HFDS may be one of most effective tools in trouble-shooting an existing control performance problem and finding an optimum solution. By comparing field data with simulation data, model parameters such as valve frictions and heat exchanger fouling resistance may be updated to match field data to repeat the behaviors. Various what-if scenarios can be explored in the simulation runs to understand problems and find solutions.