Realistic training of TPP operators
The K-Sim Engine Thermal Power Plant (TPP) simulator is based on a real thermal power plant. The main purpose of the Thermal Power Plant simulator is to train and assess operators in plant operation, including training in plant start-up and shut-down, emergency situations and safety procedures.
Compliant with industry requirements
Kongsberg Digital simulator models exceed requirements in the STCW convention, Regulation 1/12 and fulfill DNV GL’s standard DNVGL-ST-0033 for Maritime Simulator Systems.
The Thermal Power Plant model is designed to be a valuable tool in the basic and advanced training of engineers. The training objectives are to train junior engineers in basic engine room operations, senior engineers in emergency operations and troubleshooting, and to train senior and chief engineers in optimal operation, fuel economy and energy conservation. This is achieved by controlled training, leading to better understanding of the total plant operation, as a result of realistic simulation of a real engine room.
Additional training possibilities
The flexibility in K-Sim Engine Thermal Power Plant enables training and study possibilities such as:
- Test and tune control loops before implementing on a real system
- Test and modify logic in a dynamic environment
- Familiarize commissioning engineers with the plant and process dynamics
- Allow commissioning engineers to test out different start-up procedures
- Modify control and logic before installing on the real system
- Check out new controls and operating strategies
- Verify process design and study effects of modifications to the process by altering the model
- Optimize the control system and process to maximize economic performance
- Train the control operators and instrumental engineers prior to process start-up
- Familiarize and train new plant personnel before they are assigned to the plant
- Re-train experienced process operators to identify abnormal process conditions and methods of dealing with them
- Re-train experienced operators to optimize the process for maximum economic performance