Wind Turbine Noise Control via Predictive Trajectory Optimization
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Solution Overview
Problem
Wind turbines generate noise that can be problematic for neighbors, and existing control systems do not effectively account for noise emissions during operation, often requiring trade-offs between noise reduction and power output.
Innovation Solution
A method that calculates predicted operational trajectories for wind turbines, including noise measures, using model predictive control (MPC) to determine control trajectories that minimize noise impact while optimizing power output, by incorporating noise as a cost function or constraint in the optimization process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If wind turbine control systems are configured to maximize output power, then power production is improved, but noise emissions increase
Solution Approach 1:
The control system calculates predicted operational trajectories and determines noise measures in advance for future time slots before actually executing the control actions. This allows the turbine to proactively adjust operations to prevent noise violations rather than reacting after noise is generated.
Solution Approach 2:
The system dynamically adjusts control trajectories based on real-time operational state and predicted noise measures. The control approach transitions from static maximum power point tracking to dynamic trajectory optimization that adapts to changing atmospheric conditions and noise sensitivity.
2Object-generated harmful factors
If noise reduction measures are implemented, then noise emissions are reduced, but power output decreases
Solution Approach 1:
The control system uses feedback from actual operational state combined with predicted trajectories to continuously optimize the balance between noise and power. The cost function incorporates both noise measures and power production, creating a closed-loop system that adjusts control actions based on their predicted impact on both objectives.
Solution Approach 2:
The system changes operational parameters along predicted trajectories to achieve noise reduction while minimizing power loss. By optimizing the path of parameter changes rather than simply reducing power, the system maintains better overall productivity while meeting noise requirements.
3Reliability
If predictive control is used to account for future noise, then noise compliance is improved, but computational complexity increases
Solution Approach 1:
The system performs preliminary calculations of multiple predicted operational trajectories and their associated noise measures before selecting the optimal control path. This advance computation enables reliable noise compliance decisions while structuring the complexity in a manageable sequence of steps.
Solution Approach 2:
The control methodology extracts and separates the noise prediction and evaluation functions from the basic power control loop. By isolating the predictive noise assessment as a distinct computational module that feeds into trajectory selection, the system manages complexity through functional decomposition.
Data Source
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AI summary
The present invention relates to control of wind turbines where a noise measure is taken into account. Control of a wind turbine is described where a control trajectory is calculated based on noise measure, the noise measure being determined from a predicted operational trajectory. In embodiments the predicted operational trajectories are calculated by using a model predictive control (MPC) routine.