Arguably, most power industry professionals would agree that the best way to train and qualify control room operators is through implementing performance-based training that integrates a “high-fidelity” plant-specific operator training simulator (OTS) [1] [2] [3]. Today’s most effective OTS’ are installed with a virtual implementation of the reference plant’s DCS user interface and controls and have a “high-fidelity” model of the reference plant’s systems, processes and equipment.
High-fidelity simulators have the potential to provide real-to-life experience for rising field operators ensuring they learn the plant controls and procedures both effectively and in the shortest timeframe practical. The high-fidelity OTS can also be used by experienced control room operators to practice infrequently performed evolutions, practice malfunction response and learn new or updated operating procedures. From my experience as an OTS instructor, the greatest benefit of training using a high-fidelity simulator is building operator confidence that enables them to effectively deal with a myriad of operating situations through understanding both the controls and processes.
The challenge for industry management is “how should I go about purchasing a simulator that my staff will embrace.” Many will ask their control system (DCS) supplier to provide a simulator with the new or updated DCS, while others will simply work with a simulator vendor to get the simulator they want. Purchasing a simulator with a virtual version of the plant’s DCS system is no doubt the best way to get a nearly exact replica of the controls and the user interface. If the plant uses an industrial grade DCS from firms such as ABB, Siemens, Emerson, Schneider, etc., this is a streamlined process and the virtual DCS will closely replicate the plant. If the plant or processes use a PLC-based control system, the virtual solutions may not be as robust and in many cases the training functionality of the simulator will be lacking. That said, the PLC-based systems are getting better and the PLC firms will most likely make the investments to have more robust systems in the future.
The control system is critical and important for the operator to have a training experience that replicates the “look and feel” of their plant, however, equally important is the plant model. For effective training and operator “buy-in,” the modeled plant needs to react and respond to stimuli (operator and/or control system automatic inputs) nearly identical to how the actual plant would respond under similar conditions. To gain the necessary realism, high-fidelity models are required. The challenge for operations management is to know what high-fidelity truly means and how to ensure the simulator purchased is truly high-fidelity.
The term “high-fidelity” indicates that the processes will be based on first principles engineering models derived from dynamic mass, energy and momentum balances. This means that the mathematical models will be based closely on physics, chemistry and thermodynamic equations without the use of empirical equations, look up tables and parameter fitting (basically approximations of the true energy transfers and processes taking place in the model). The value of using first principles models is that the modeled plant will respond accurately regardless of the operating conditions of the plant. On simulators that rely heavily on approximations they generally look good when doing routine startup and shutdown operations, however, as soon as the plant is in an off-normal condition, “weird” things start to happen in the model, unrealistic data appears on the operator user interface and the realism is lost. In worst-case scenarios this can lead to negative training and lack of confidence that the simulator is actually effective.
To eliminate the lost opportunities that can arise from a limited fidelity simulator, a comprehensive simulator technical specification is needed to identify goals and expectations of the simulator clearly. The specification should be developed based on an assessment of the plant personnel, systems and processes and define goals and objectives for the simulator. On a system and component specific level, the specification should identify expected modeling requirements and any unique conditions or responses that are relevant to the reference plant. Identifying system and component level modeling requirements in the simulator specification will eliminate simplifications that may impact achieving the training objectives and at the same time allow for simplification of the models in areas of the plant that the training value would be minimal. A key component of the specification should be to identify the simulator validation and testing requirements, so the simulator is thoroughly evaluated and tested.
Once the specification is used to obtain vendor proposals and a contract is awarded, it is critically important that the specification is used as “road map” for implementing the simulator development project and as a way to validate that the simulator and controls vendors are building a simulator that will meet the defined goals and objectives.
A structured and organized simulator specification will lead to procuring a simulator that will achieve management’s objectives and result in achievement or all training goals and objectives. Without taking the time upfront to identify what training objectives need to be met and the modeling requirements for each plant system, the simulator will have limited training value and it is difficult to hold the simulator vendor accountable for delivering the specific realism that is needed.
[1] https://www.powermag.com/operator-qualification-and-training-for-the-power-industry/
[2] https://www.powermag.com/power-plant-training-simulators-explained/
[3] https://www.power-eng.com/articles/print/volume-122/issue-6/features/using-simulation-to-drive-cultural-change-and-operational-excellence.html
