The Operator Training Simulator (OTS) is by far the most efficient way of training, as it reduces the training time from months to days.
Ideally, the OTS interface shall be a replica of the HMI of the plant control system. The latter shall be completely replaced with the plant digital twin (PDT). Its specification is defined by the OTS objectives, which address both normal and abnormal operations.
The normal one includes the following scenarios.
- Unit startup and shutdown
- Change in demand
- Unit unloading to the lowest stable levels of operation
- Scheduling of routine intermittent operations
Unlike the former, the list of abnormal (off-design) operation scenarios is infinite. Its top-priority entries are as follows.
- loss of measurement
- alarm/interlock corrective action (troubleshooting)
- loss of control or its malfunction
- operation sequence failure
- alarm flooding
- equipment and piping leaks and bursts
- external disruptions (power loss, seawater high SDI, turbidity)
High-fidelity PDT
To gain the necessary realism, PDT shall accurately simulate the dynamic behavior of the plant's key components and overall process. The only way to build such a twin is to use first-principles engineering models derived from dynamic mass, energy and momentum balances and adjusted to the equipment's actual performance curves (of pumps, filters, reverse osmosis membranes, remineralization reactors) reflecting the performance degradation-restoration cycles. PDT must realistically react to changes in feed water salinity, temperature, SDI, or turbidity. Next, PDT shall model the equipment and instrumentation failures as a function of the plant operation time. It can’t be neglected in building high-fidelity OTS.
Abnormal operation modeling
The cornerstone question is whether the abnormal operation is the OTS input (by the instructor) or the PDT output (as a result of equipment failure or wear and tear).
The former approach dominates in the process plants due to its simplicity. As it breaks down the cause-and-effect logic, possibilities are limited to emulate in OTS decision-making regarding ways of troubleshooting and handling alarm flooding.