Inoperability Duration Determination for Offshore Wind Assets
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Solution Overview
Problem
Offshore wind farms face challenges in assessing and mitigating risks associated with natural and non-natural adverse events, which can lead to inoperable periods and significant financial losses due to the complexity of interdependent generation, transmission, and storage assets.
Innovation Solution
A method to determine the average annual duration of inoperability for energy generation, transmission, or storage assets by calculating probabilities of natural and non-natural adverse events, their severities, and damage states, allowing for the estimation of average annual financial losses and repair times, using geolocator information, drone or satellite imagery, and IoT devices for asset monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive risk assessment is performed for offshore wind farms considering natural and non-natural adverse events, then reliability of power supply is improved, but complexity of assessment process increases
Solution Approach 1:
The risk assessment process is segmented into distinct modules: natural adverse event assessment (cyclones, storms, earthquakes) and non-natural adverse event assessment (corrosion, metal fatigue, cyber attacks). Each module independently evaluates specific risk categories, making the overall complex assessment process more manageable and systematic while comprehensive.
Solution Approach 2:
The method performs preliminary actions by pre-calculating probabilities of adverse events and their associated damages before actual failures occur. By estimating the likelihood and impact of potential risks in advance, the system enables proactive risk mitigation rather than reactive response, improving reliability while structuring complexity into predictable assessment steps.
2Measurement precision
If probability of adverse events and damage states are calculated for all assets, then accuracy of inoperability determination is improved, but time required for assessment increases
Solution Approach 1:
The method changes parameters by using probability values and severity scores that can be calibrated and updated. By expressing risks in terms of probabilities and damage state categories, the system achieves accurate assessments that can be efficiently calculated and compared, balancing precision with computational efficiency.
Solution Approach 2:
The assessment framework creates a standardized model that can be replicated across different assets and locations. By establishing universal assessment procedures and damage state categories, the system maintains high accuracy while reducing the time required to assess each individual asset through standardized templates and procedures.
3Reliability
If repair time and financial loss are estimated for each adverse event, then completeness of risk assessment is improved, but complexity of data processing increases
Solution Approach 1:
The data processing is segmented into distinct categories: natural adverse events (cyclones, storms, earthquakes) and non-natural adverse events (corrosion, metal fatigue, cyber attacks). Each category has its own processing workflow for estimating repair times and financial losses, which simplifies the overall data processing complexity while maintaining comprehensive assessment coverage.
Solution Approach 2:
The method uses simplified estimation models and standardized data structures that can be quickly processed and updated. By employing readily available data sources and straightforward calculation frameworks, the system achieves complete risk assessment without requiring complex proprietary data processing systems, reducing data processing complexity while maintaining thoroughness.
Data Source
AI summary
A method of determining an average duration for a time period that the at least one first asset, or a second asset operatively connected to the at least one first asset, is inoperable is described. The method comprises obtaining a location of at least one first asset associated with energy generation, transmission or storage. The method comprises obtaining a first probability of a natural adverse event occurring at the location of the at least one first asset. The method comprises obtaining a second probability of a non-natural adverse event occurring at the location of the at least one first asset. The method comprises determining a third probability of at least one damage state of the at least one first asset from the first and second probabilities. The method comprises determining an average duration for a time period that the at least one first asset, or a second asset operatively connected to the at least one first asset, is inoperable based on the third probability of the at least one damage state of the first asset.