Wind Turbine Control Models for Real-Time High-Fidelity Estimation
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Solution Overview
Problem
Conventional wind turbine control models lack the fidelity needed for improved control system design and aerodynamic modeling due to limited computational capabilities, relying on simplified assumptions that result in inaccurate performance and limited energy production.
Innovation Solution
Development of high-fidelity wind turbine control models that provide a rigorous physical representation of structural dynamics and aerodynamics, incorporating advanced mechanical and aerodynamic equations, including flexible blade representation, induced velocities, and fluid/structure interaction, while operating on limited computational power, using partitioned models and dynamic wake effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If simplified quasi steady aerodynamics models with lookup tables are used in control models, then computational cost is reduced and real-time operation is enabled, but model fidelity and accuracy deteriorate
Solution Approach 1:
The patent segments the high-fidelity aerodynamic model into computationally intensive components (full 3D unsteady aerodynamics with dynamic wake effects) and computationally light components (structural dynamics), evaluating only the essential parts in real-time while pre-computing or approximating others. This selective segmentation enables real-time operation while preserving critical accuracy.
Solution Approach 2:
The patent changes the parameter representation from static lookup tables to dynamic state variables that evolve according to physical laws. By representing aerodynamic states as time-varying parameters governed by differential equations rather than fixed tables, the model achieves both accuracy and computational efficiency suitable for real-time control.
2Measurement precision
If high-fidelity models with multiple degrees of freedom are used, then predictive accuracy of transient behavior is improved, but computational complexity increases making real-time control difficult
Solution Approach 1:
The patent extracts and retains only the essential degrees of freedom that dominate wind turbine transient behavior (tower fore-aft bending, blade flapwise bending, drive-train torsion) while eliminating less significant modes. This selective extraction maintains predictive accuracy for critical transient responses while reducing computational complexity to levels suitable for real-time control applications.
Solution Approach 2:
The patent implements a dynamic model that adapts its complexity based on operating conditions, activating only the necessary degrees of freedom and aerodynamic effects relevant to current transient events. This dynamic approach reduces computational complexity during steady operation while maintaining high fidelity during transient conditions requiring accurate prediction.
3Ease of operation
If conventional simplified control models are used, then computational capabilities are within limits of industrial control platforms, but control system performance and energy production are limited
Solution Approach 1:
The patent replaces traditional mechanical lookup table-based aerodynamic models with a physics-based dynamic aerodynamic model that uses fundamental aerodynamic equations. This substitution maintains computational feasibility on industrial platforms while significantly improving control performance and energy production through more accurate physical representation.
Solution Approach 2:
The patent creates a unified control model that simultaneously serves multiple functions: real-time state estimation, control optimization, and performance prediction. This multi-functional model eliminates the need for separate simplified models for different purposes, achieving both computational efficiency and improved energy production within existing industrial control platform capabilities.
Data Source
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AI summary
A system for computing wind turbine estimated operational parameters and/or control commands, includes sensors monitoring the wind turbine, a control processor implementing a model performing a linearization evaluation to obtain a structural component dynamic behavior, a fluid component dynamic behavior, and/or a combined structural and fluid component dynamic behavior of wind turbine operation, and a module performing a calculation utilizing the linearization evaluation of the structural component dynamic behavior, the fluid component dynamic behavior, and/or the combined structural and fluid component dynamic behavior. The module being at least one of an estimation module and a multivariable control module. The estimation module generating signal estimates of turbine or fluid states. The multivariable control module determining actuator commands that include wind turbine commands that maintain operation of the wind turbine at a predetermined setting in real time. A method and a non-transitory medium are also disclosed.