Power Plant Model Tuning for Generating Unit Optimization
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Solution Overview
Problem
Power plant operators face challenges in maximizing economic return due to the complexity of modern power plants with multiple generating units, as conventional control systems lack the ability to effectively accommodate changing conditions and variability, leading to inefficient operation and underutilization of resources.
Innovation Solution
A control method that involves tuning a power plant model based on measured operating parameters and simulating proposed operating modes to optimize performance, using a combination of physical and economic models to predict performance under varying conditions and identify optimal operating setpoints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional control systems are used to manage power plant generating units, then the system structure remains simple and easy to operate, but the system cannot effectively accommodate changing conditions and variability, leading to inefficient operation and underutilization of resources
Solution Approach 1:
The control system transitions from static to dynamic operation through continuous model tuning. The power plant model is dynamically adjusted using real-time measured operating parameters, allowing the system to adapt to changing conditions and maximize efficiency without requiring complete system redesign.
Solution Approach 2:
The system implements continuous feedback loops where measured operating parameters are compared against model predictions, and the model is tuned based on the differential between measured and predicted values. This feedback mechanism enables the control system to learn from actual plant performance and improve operational efficiency over time.
2Adaptability or versatility
If static control profiles are used for thermal generating units, then the control system remains simple, but the system cannot account for machine degradation and variable operating conditions, resulting in suboptimal performance
Solution Approach 1:
The system performs preliminary model tuning using historical measured operating parameters before actual operation. By pre-tuning the power plant model with past performance data, the system prepares optimized control strategies in advance, enabling better adaptation to future operating conditions without adding complex real-time control mechanisms.
Solution Approach 2:
The control system serves itself by automatically tuning the power plant model using its own measured operating parameters. The system uses its internal resources and data to improve its own performance, eliminating the need for external intervention or complex manual adjustment mechanisms.
3Measurement precision
If periodic performance tests are used to update control profiles, then the process remains simple and infrequent, but the system cannot capture real-time degradation and performance changes, leading to outdated control parameters
Solution Approach 1:
The system implements continuous model tuning using ongoing measured operating parameters rather than periodic updates. This continuous process ensures the power plant model remains current with actual performance conditions without requiring time-consuming periodic shutdowns for testing and recalibration.
Solution Approach 2:
The system performs model tuning in advance using historical data before performance degradation significantly impacts operation. By continuously preparing updated models based on accumulating measured parameters, the system proactively maintains optimal performance rather than reactively responding to degradation.
Data Source
AI summary
A control method for optimizing or enhancing an operation of a power plant that includes thermal generating units for generating electricity. The power plant may include multiple possible operating modes differentiated by characteristics of operating parameters. The method may include tuning a power plant model so to configure a tuned power plant model. The method may further include simulating proposed operating modes of the power plant with the tuned power plant model. The simulating may include a simulation procedure that includes: defining a second operating period; selecting the proposed operating modes from the possible operating modes; with the tuned power plant model, performing a simulation run for each of the proposed operating modes whereby the operation of the power plant during the second operating period is simulated; and obtaining simulation results from each of the simulation runs.