Wind Farm Load Control Using Site-Specific Flow Field Modeling
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Solution Overview
Problem
Current wind farm design fails to account for site-specific turbine loads influenced by terrain and atmospheric conditions, leading to high component failure rates due to inadequate understanding and measurement of wind flow quality, which is costly and labor-intensive.
Innovation Solution
A method to compute farm-level flow fields and local loads using existing turbine sensors, allowing for the derivation of site-specific loads and flow quality, without the need for additional measurements, by collating data from all turbines and using it to modify control strategies for extended turbine life, increased energy production, and reduced operational costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If strain gauges are attached to turbines for loads measurement, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent uses existing anemometer measurements as a proxy or copy to infer loads, rather than directly measuring loads with strain gauges. By creating a correlation model between wind speed measurements and actual loads, the system achieves load estimation without physical load sensors, thereby reducing complexity while maintaining useful measurement precision
Solution Approach 2:
The patent replaces the mechanical strain gauge measurement system with a computational approach using existing wind speed sensors and flow field models. Instead of mechanically measuring loads through strain gauges, the system uses aerodynamic models and wind field data to calculate estimated loads, substituting mechanical measurement with computational analysis
2Measurement precision
If strain gauges are attached to turbines for loads measurement, then measurement precision is improved, but labor intensity and cost increase
Solution Approach 1:
The patent uses existing anemometer measurements as a proxy to infer loads, avoiding the need for physical installation of strain gauges. This copying approach allows load estimation using already-deployed sensors, eliminating the labor-intensive measurement campaigns required for strain gauge installation while maintaining useful measurement precision
Solution Approach 2:
The system uses the wind turbine's own existing sensors (anemometers) to generate load information, making the turbine self-sufficient for load monitoring. This eliminates the need for external measurement campaigns and specialized installation teams, significantly improving ease of manufacture and deployment
3Device complexity
If only one or two turbines are instrumented for loads measurement, then cost is reduced, but measurement coverage and reliability decrease
Solution Approach 1:
The patent merges data from multiple turbines' existing anemometers to create a comprehensive farm-level flow field model. By combining wind speed measurements from numerous turbines across the farm, the system achieves complete farm-level coverage and improved reliability, eliminating the limitation of single-turbine or limited-turbine instrumentation
Solution Approach 2:
The patent makes the existing anemometer network serve multiple functions: not only yaw control but also farm-level flow field characterization and load estimation for all turbines. This multi-functionality allows the same sensor infrastructure to provide both operational control and research/monitoring capabilities across the entire farm, improving reliability without additional instrumentation
4Device complexity
If anemometer data alone is used, then device complexity is reduced, but flow quality assessment capability is insufficient
Solution Approach 1:
The patent introduces a flow field model as an intermediary between raw anemometer data and flow quality assessment. The model processes and interprets the simple wind speed measurements, extracting flow quality characteristics that are not directly observable from single-point anemometer readings, thereby enhancing measurement precision without adding complex sensors
Solution Approach 2:
The patent transitions from single-point anemometer measurements to a distributed three-dimensional flow field representation by combining data from multiple turbines at different locations and heights. This dimensional expansion allows assessment of flow quality across the entire rotor disc area and throughout the farm, providing comprehensive flow quality evaluation using only existing sensors
Data Source
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AI summary
A method for controlling wind turbine farm level loads by control strategy through site-specific topology effects. The method involves the steps of: providing wind velocity data from wind sensors mounted on the wind turbines, the velocity data comprising wind speed and wind direction; providing wind velocity data from one or more reference sensors, the velocity data comprising wind speed and wind direction; binning the wind data according to wind speed and wind direction; identifying wind turbines in which the velocity data deviates from the reference; and calculating modified loads acting on the wind turbines where the velocity data deviates from the reference; whereby the control strategy and/or maintenance activities are revised. A method for extending (or reducing) life of a wind turbine, altering performance (increased Annual Energy Production, AEP) (operational), or reducing cost through structural material reduction (design) is further disclosed. The approach can be used for scheduling maintenance for wind turbines in a wind farm.