Wind Turbine Test System for Parameter Optimization
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Solution Overview
Problem
Existing wind turbines often operate sub-optimally due to default parameter settings that do not account for irregularities in components and seasonal variations in environmental conditions, leading to inefficient energy conversion and potential component fatigue.
Innovation Solution
A test system that randomly selects and iterates through test points to measure operational parameters, allowing for the selection of optimal values by reducing skewing from environmental changes and providing robust data for downstream analysis, using a controller and measurement devices to adjust and monitor wind turbine operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If default parameter values are used during installation, then setup time is reduced, but operational efficiency deteriorates due to component irregularities and environmental variations
Solution Approach 1:
The system automatically adjusts operational parameters (such as rotor speed, pitch angle, and generator torque) based on real-time measurements of component actual values and environmental conditions. This dynamic parameter optimization resolves the contradiction by maintaining high operational efficiency without requiring manual setup time investment.
2Productivity
If parameter optimization testing is conducted, then operational efficiency is improved, but testing time and complexity increase
Solution Approach 1:
The system performs preliminary automated measurements of component actual values (such as gear ratios, blade pitch characteristics, and generator parameters) during installation. These pre-measured values are stored and used as the basis for automatic parameter optimization, eliminating the need for time-consuming manual testing while ensuring operational efficiency.
Solution Approach 2:
The control system automatically uses the measured component actual values to calculate and adjust optimal operational parameters without requiring external testing or manual intervention. The system self-optimizes by processing its own measurement data, thereby improving operational efficiency without adding testing time.
3Device complexity
If component irregularities are not accounted for, then system complexity is reduced, but energy conversion efficiency deteriorates
Solution Approach 1:
The system continuously measures actual component values (such as actual gear ratios and blade characteristics) and feeds this information back to the control algorithm. The controller then adjusts operational parameters in real-time to compensate for component irregularities, maintaining high energy conversion efficiency without requiring complex manual calibration procedures.
Data Source
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AI summary
A test system (300) for a wind turbine (100) is provided. The test system includes at least one measurement device (306) configured to measure at least one operating condition of the wind turbine, and a controller (202) communicatively coupled to the measurement device. The controller is configured to execute a wind turbine test (400) including defining a plurality of test points (404) for at least one wind turbine operational parameter (402), each test point including at least one test value (410) for the wind turbine operational parameter, determining a randomized test sequence (416) of the plurality of test points, iterating through the randomized test sequence, and measuring the operating condition of the wind turbine at each test point.