Forecasting Startup Time for Combined Cycle Power Systems
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Solution Overview
Problem
Combined cycle power generation systems face inefficiencies in startup scheduling due to conservative template-based forecasting, leading to premature reaching of dispatchable load, unnecessary fuel consumption, and sub-optimal power generation, driven by the complexity of accurately predicting startup duration based on varying operational conditions.
Innovation Solution
A computer control system that inputs desired startup time and current operational conditions to generate a precise forecasted start time for combined cycle power generation systems, utilizing historical data and algorithms to optimize startup sequences for gas and steam turbines, ensuring the system reaches dispatchable load at the scheduled time with minimal fuel usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conservative template-based forecasting is used to determine startup time, then the system ensures that dispatchable load is reached no later than needed, but the system reaches dispatchable load prematurely and consumes fuel unnecessarily
Solution Approach 1:
The system changes the parameter of startup time forecasting from static template-based values to dynamic condition-based predictions. By monitoring real-time operational parameters (steam turbine temperature, gas turbine status, ambient conditions) and adjusting the forecasted startup duration accordingly, the system optimizes the startup schedule to reach dispatchable load exactly when needed, minimizing fuel consumption while ensuring reliability.
2Loss of energy
If accurate condition-based startup scheduling is implemented, then fuel consumption is minimized and startup duration is optimized, but the complexity of forecasting and calculating startup duration increases
Solution Approach 1:
The system uses historical startup data and operational patterns as templates to create predictive models. By copying and analyzing past startup sequences under various conditions, the system builds databases of startup durations correlated with specific operational states. This allows accurate condition-based forecasting without requiring complex real-time calculations, reducing system complexity while maintaining optimization benefits.
3Measurement precision
If manual calculation of accurate startup schedules is performed, then optimal startup timing can be achieved, but the process becomes laborious and complicated
Solution Approach 1:
The system enables operators to input basic current operational conditions (steam turbine temperature, gas turbine status), and the system automatically performs the complex forecasting and calculation tasks. The algorithm independently analyzes the input conditions, queries historical databases, computes the optimal startup time, and presents the result to the operator. This self-service approach maintains high measurement precision while dramatically reducing operator workload and complexity.
4Productivity
If generic startup templates are used for broad ranges of initial conditions, then schedule preparation is expedited, but the templates predict significantly longer startup periods than actual
Solution Approach 1:
The system transitions from using single generic templates for broad condition ranges to providing localized, condition-specific startup duration predictions. By segmenting the operational condition space into distinct states (e.g., cold startup, warm startup, hot startup based on steam turbine temperature) and assigning specific forecasted durations to each state, the system maintains quick schedule preparation while eliminating excessive time margins associated with conservative generic templates.
Data Source
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AI summary
A method for forecasting a start period for a combined cycle power generation system (10) including a gas turbine engine (12), a steam turbine (16) and a computer control system (22) including a user input device (26) and an output device (24), the method including: inputting (144) a desired time (38) at which the combined cycle power generation system is to reach a dispatchable load; acquiring a current value (124) of a predetermined operational condition of the combined cycle power generation system; the computer control system executing an algorithm which generates a forecasted start time (150) based on the desired time and the current value, wherein the combined cycle power generation system is predicted to be at the dispatchable load at the desired time when started at the forecasted start time, and the computer system outputting (148) the forecasted start time to the output device.