Wind Turbine Update Validation Using Statistical Load Envelopes
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Wind turbine performance is affected by structural and software updates, leading to potential load performance degradation, which existing technologies struggle to mitigate effectively.
Innovation Solution
A method using statistical analysis to validate second versions of software or structural models for wind turbines by simulating load performance with and without the updates, determining statistical parameters to assess load variations, and validating the updates based on predefined criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If structural model or software updates are deployed to improve wind turbine performance, then operational efficiency and power output can be enhanced, but load performance degradation and structural integrity risks may occur
Solution Approach 1:
The patent performs load simulations and statistical comparisons before deploying software or structural model updates to wind turbines. By conducting preliminary validation using confidence interval methods, the system identifies potential load performance degradation risks before they occur in actual operation, allowing preventive measures to be taken while still enabling performance improvements through validated updates.
2Reliability
If comprehensive load simulations are performed to validate software or structural model updates, then the risk of load performance degradation is reduced, but the time and effort required for validation increases
Solution Approach 1:
The patent transforms the validation approach by changing from deterministic load comparison to statistical parameter analysis. By using confidence intervals and statistical methods to compare load parameters between updated and baseline models, the system achieves rigorous validation without requiring exhaustive simulation of all possible operating conditions, thereby reducing validation time while maintaining reliability.
3Measurement precision
If statistical methods are used to quantify load variations, then the distinction between stochastic variations and update-induced changes is clarified, but the complexity of the validation process increases
Solution Approach 1:
The patent introduces statistical confidence intervals as an intermediary tool to bridge the gap between stochastic load variations and deterministic update effects. This statistical mediator allows the system to distinguish between natural load fluctuations and genuine performance degradation caused by updates, providing clear decision criteria without requiring complex causal analysis of each individual load variation.
Data Source
AI summary
Disclosed is a method, performed by an electronic device, for validation of a second version of a software or a second structure model for control of a wind turbine. The method comprises obtaining first load data from simulating a load of the wind turbine using a first structural model and a first version of the software. The method comprises obtaining second load data from simulating the load of the wind turbine using the first structural model and the second version of the software or using the first version of the software and a second structural model. The second version of the software is an update of the first version of the software. The second structural model is an update of the first structural model. The method comprises determining, based on the first load data and the second load data, a statistical parameter.