Wind Turbine Yaw Coordination for Wake Steering and Misalignment Correction
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Solution Overview
Problem
Existing wind farm operations underperform due to wake effects from upstream turbines, inaccurate yaw control, and uncorrected yaw misalignment, leading to reduced power output and increased maintenance costs.
Innovation Solution
A coordinated yaw control system that utilizes data from multiple turbines to determine overall wind direction, correct yaw misalignment, and implement dynamic wake steering, optimizing nacelle positions across the wind farm for improved energy production.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple wind turbines are installed in close proximity to maximize land use and energy production, then the overall energy output increases, but wake effects from upstream turbines reduce downstream turbine performance by up to 15%
Solution Approach 1:
The patent converts the harmful wake effect into a beneficial control mechanism by intentionally yawing upstream turbines to steer wakes away from downstream turbines. This transforms the natural wake phenomenon from a pure loss into a controllable parameter that can be optimized for overall farm performance, achieving 3-5% energy production improvement.
Solution Approach 2:
The system implements dynamic wake steering control where upstream turbines continuously adjust their yaw angles based on real-time wind conditions and downstream turbine performance. This dynamic adjustment allows the wind farm to adapt to changing atmospheric conditions and maximize energy capture throughout the day.
2Ease of operation
If individual turbines use local wind direction measurements for yaw control, then each turbine can independently optimize its own performance, but the wake steering cannot be achieved effectively because local measurements do not reflect overall wind direction
Solution Approach 1:
The patent merges individual turbine wind direction measurements with LIDAR-based remote sensing data to create a comprehensive picture of the wind field. By combining local anemometer data with upstream wind measurements from LIDAR, the system achieves both independent turbine control and accurate overall wind direction detection for effective wake steering.
Solution Approach 2:
The system introduces LIDAR as an intermediary measurement tool that directly measures wind velocity vectors upstream of the turbine array. This intermediary provides accurate wind direction information that mediates between individual turbine local measurements and the overall farm-level wind field, enabling precise wake steering control.
3Device complexity
If traditional yaw control systems are used, then the system structure remains simple, but the yaw control response is slow and inaccurate, making real-time wake steering less effective
Solution Approach 1:
The system performs preliminary wind field assessment using LIDAR upstream of the turbine array before turbines need to respond. This advance measurement allows the control system to prepare wake steering commands in advance, improving response speed without requiring complex modifications to the actual yaw control mechanism.
Solution Approach 2:
The patent implements a feedback control loop where LIDAR measures upstream wind conditions, the control system calculates optimal yaw angles for wake steering, and turbine yaw positions are adjusted accordingly. Downstream turbine performance feedback further refines the control, creating a closed-loop system that continuously optimizes wake steering effectiveness.
Data Source
AI summary
Systems and methods of autonomous farm-level control and optimization of wind turbines are provided. Exemplary embodiments comprise a site controller running on a site server. The site controller collects and analyzes yaw control data of a plurality of wind turbines and wind direction data relating to the plurality of wind turbines. The site server determines collective wind direction across an area occupied by the plurality of wind turbines and sends yaw control signals including desired nacelle yaw position instructions to the plurality of wind turbines. The site controller performs wake modeling analysis and determines desired nacelle positions of one or more of the plurality of wind turbines. The desired nacelle yaw position instructions systematically correct static yaw misalignment for all of the plurality of wind turbines. Embodiments of the disclosure provide means to perform whole site or partial site level controls of the yaw controllers of a utility scale wind turbine farm. The overall effect of the coordinated yaw control of wind turbines across the whole or partial site is intended to keep the wake loss of the wind turbines from the upstream wind turbines to the minimum and to maximize the production of turbines that are not waking other turbines.