Wind Turbine Power Boost via Model Predictive Control
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Solution Overview
Problem
Existing wind turbine control methods are inadequate for managing power boosts and recovery periods effectively, particularly in ensuring optimal operation within safe limits and minimizing fatigue loads during increased power production.
Innovation Solution
The implementation of a model predictive control (MPC) routine that calculates and controls predicted operational trajectories for wind turbines, using a receding horizon approach to manage power boosts and recovery periods, ensuring optimal operation and adherence to operational constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If kinetic energy is used to boost power production during grid stabilization events, then electrical power output increases, but rotor speed decreases and fatigue loads increase
Solution Approach 1:
The control system dynamically adjusts pitch angle and converter power reference in real-time during boost events, transitioning from static control strategies. The MPC controller continuously optimizes control parameters based on current rotor speed, power output, and predicted future states, enabling adaptive response to changing operational conditions while managing fatigue loads
Solution Approach 2:
The system changes operational parameters (pitch angle, converter power reference, torque reference) to optimize performance during boost events. By dynamically adjusting these parameters based on predicted trajectories and current state, the system achieves desired power output while constraining fatigue load increases within acceptable limits
2Productivity
If model predictive control is implemented to optimize power boost trajectories, then power production efficiency increases, but control system complexity increases
Solution Approach 1:
The MPC controller performs preliminary calculations of predicted operational trajectories before executing control actions. By pre-computing optimal pitch and power reference trajectories based on current state and future predictions, the system prepares control sequences in advance, enabling efficient real-time execution without excessive computational burden during critical boost events
Solution Approach 2:
The patent replaces traditional mechanical control approaches with model-based computational control. Instead of relying on purely mechanical or simple PID control systems, the invention uses MPC algorithms that substitute complex computational models and predictions for simpler control mechanisms, achieving superior optimization with manageable complexity through software-based solutions
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
This solution enables wind turbines to efficiently increase power production during boost periods while minimizing impact on recovery periods and maintaining safe operational limits, reducing fatigue loads and ensuring optimal performance.
Implementation Method 1
the kinetic energy stored in the rotating system may be used for grid stabilization. This is sometimes referred to as the wind turbine may provide inertial response. The stored kinetic energy may be used to boost the generated power from the normal production for a short period of time
Data Source
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AI summary
The present disclosure relates to a control of a wind turbine in connection with power boosting or fast increase of active power production. A boost command is received (63) and based on the current operational state and the boost level a predicted control trajectory is calculated using a model predictive control (MPC) routine (64). The wind turbine is controlled using the calculated control trajectory during the power boost (65).