Turbine Starting Controller Optimizes Thermal Stress Prediction
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Solution Overview
Problem
Conventional turbine starting controllers face challenges in minimizing thermal stress on turbine rotors during rapid start/stop operations, leading to reduced rotor life and difficulty in achieving optimal starting times due to high computational complexity and inaccurate determination of manipulated variables.
Innovation Solution
A turbine starting controller that predicts thermal stress by taking the turbine acceleration rate/load increase rate as a directly manipulated variable, simplifying optimization calculations by assuming a constant rate, and using linear interpolation to determine the optimum manipulated variable, thereby reducing computational complexity and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If rapid start/stop operations are performed to improve productivity, then turbine starting time is reduced, but thermal stress on the rotor increases excessively
Solution Approach 1:
The system performs preliminary calculation of the manipulated variable (turbine acceleration rate) before actual startup occurs. By pre-calculating the optimal acceleration rate that will result in thermal stress exactly at the prescribed limit value, the system prepares the control strategy in advance, enabling rapid startup while preventing excessive thermal stress through proactive rather than reactive control.
Solution Approach 2:
The system uses feedback from thermal stress predictions to adjust the manipulated variable. By continuously monitoring predicted thermal stress and comparing it against the prescribed limit, the system dynamically adjusts the turbine acceleration rate to maintain thermal stress within acceptable limits while achieving rapid startup, creating a closed-loop control system that balances speed and stress.
2Measurement precision
If conventional optimization calculation is performed with multiple variables to improve control accuracy, then thermal stress prediction accuracy improves, but computational complexity increases excessively
Solution Approach 1:
The system extracts and isolates the manipulated variable (turbine acceleration rate) as the sole optimization variable, separating it from other control parameters. By focusing optimization calculation only on determining the optimal manipulated variable rather than simultaneously optimizing multiple variables, the system achieves sufficient thermal stress prediction accuracy while dramatically reducing computational complexity to levels suitable for real-time control.
3Ease of operation
If manipulated variable is determined from plant state variable deviation to simplify control, then control implementation is easier, but optimization performance becomes unsatisfactory
Solution Approach 1:
The system introduces thermal stress prediction as an intermediary between the manipulated variable and plant state variables. Instead of directly determining the manipulated variable from state variable deviation (which yields poor optimization), the system uses thermal stress prediction as a mediator to evaluate the impact of manipulated variable changes on rotor thermal stress, thereby achieving both implementable control and satisfactory optimization performance through this intermediate evaluation layer.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution enables the shortest turbine starting time while maintaining thermal stress within prescribed limits, enhancing the accuracy and reliability of starting control and reducing computational complexity.
Implementation Method 1
the surface metal temperature of a turbine rotor rises as the heat transfer rate between the steam and the rotor improves due to a rise in the temperature of inflow steam and an increase in steam flow
Implementation Method 2
The temperature of the inner portion of the turbine rotor rises due to the conduction of heat from the rotor surface
Data Source
AI summary
A turbine starting controller includes: an optimum starting control unit for predicting, while taking as a variable a turbine acceleration rate/load increase rate as a directly manipulated variable, thermal stress generated in a turbine rotor over a prediction period from a current time to the future, calculating for each control cycle a manipulated variable optimum transition pattern in the prediction period which makes a turbine starting time shortest while keeping the predicted thermal stress equal to or lower than a prescribed value, and determining as an actual optimum manipulated value a value at the current time in the manipulated variable optimum transition pattern; and an rpm/load control unit to which the optimum manipulated variable from the optimum starting control unit is input, for controlling the drive of control valves.