Wind Turbine Fatigue Load Estimation Using Operational Metadata
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Solution Overview
Problem
Existing methods for determining fatigue loads in wind turbines do not adequately account for grid situations, leading to increased uncertainty in lifetime estimation and potential premature failure due to unconsidered load increases during transient grid events.
Innovation Solution
A method and system that utilize operational metadata from wind turbine control systems to determine fatigue loads by comparing current operational situations to a database of predefined situations, allowing for accurate estimation without additional sensors, and incorporating grid events into the analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing methods for determining fatigue loads are used, then the determination process is simple, but the reliability of lifetime estimation deteriorates due to unconsidered grid events
Solution Approach 1:
The patent applies preliminary action by pre-defining operational situations and their corresponding fatigue loads before actual operation. The system pre-processes and stores metadata patterns that represent typical operational states, so when during operation a current state matches a predefined pattern, the corresponding fatigue load can be directly retrieved without complex real-time calculations. This resolves the contradiction by preparing information in advance, improving reliability while keeping the actual determination process simple.
Solution Approach 2:
The patent uses copying by creating a database of predefined operational situations that replicate real-world operating conditions. Instead of measuring actual complex physical loads during operation, the system copies representative operational metadata patterns and their associated fatigue loads into a database. During operation, the system finds matching patterns in the database and uses the copied fatigue load information, achieving reliable lifetime estimation without complex real-time measurement systems.
2Measurement precision
If additional sensors are installed to capture grid events, then measurement precision improves, but device complexity and cost increase
Solution Approach 1:
The patent applies self-service by utilizing operational metadata that is already generated and collected by the wind turbine's existing control systems for other purposes (monitoring, control, etc.). Instead of installing additional sensors to capture operational states, the system serves itself by reusing the metadata that already exists in the control system. This resolves the contradiction by achieving precise operational situation detection without adding any hardware complexity.
Solution Approach 2:
The patent demonstrates universality by making the existing operational metadata collection system serve multiple functions. The same metadata infrastructure that supports basic turbine control and monitoring is also used for fatigue load determination and lifetime estimation. By finding multiple uses for the existing data collection capability, the system achieves precise measurement of operational situations without the need for dedicated sensors or additional hardware.
3Measurement precision
If comprehensive operational metadata is collected and analyzed, then fatigue load determination accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-processing operational metadata and pre-defining operational situations with their corresponding fatigue loads before actual fatigue determination is needed. The system creates a ready-reference database of operational patterns and their associated fatigue characteristics in advance. During operation, instead of processing raw metadata in real-time, the system performs simple pattern matching against the pre-processed database, dramatically reducing processing time while maintaining high accuracy through the comprehensive nature of the pre-analyzed data.
Data Source
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AI summary
The present disclosure relates to methods and systems for determining fatigue loads in a wind turbine. Such a method may comprise obtaining operational metadata representative for an operational situation, and determining whether the operational metadata corresponds to operational metadata from one of a plurality of previously defined operational situations for which fatigue loads are known, the plurality of previously defined operational situations being stored in an operational situations database. If the operational metadata representative for the operational situation substantially corresponds to operational metadata from the stored previous operational situation, then the fatigue loads for the stored previously define operational situation are summed to historically accumulated fatigue loads to determine total accumulated fatigue loads. Methods for registering an operational situation in a wind turbine are also provided.