Wind Turbine Power Scheduling for Fatigue Life Trade-Offs
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Solution Overview
Problem
Wind turbines face challenges in optimizing energy capture while managing fatigue loads, leading to reduced lifetime and increased maintenance due to over-rating, which increases wear and tear on components.
Innovation Solution
A method for generating a control schedule that balances energy capture and fatigue life by determining the current remaining fatigue lifetime of turbine components, applying optimization functions to vary the control schedule, and constraining it with input constraints such as component replacements and lifetime targets, allowing for flexible operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If wind turbine operates at maximum power level continuously, then Annual Energy Production is maximized, but fatigue lifetime of components is reduced
Solution Approach 1:
The patent implements dynamic adjustment of power reference values based on real-time fatigue lifetime estimates. The control schedule is not static but adapts continuously to current component conditions, wind conditions, and remaining fatigue life, allowing the turbine to operate at optimal power levels that balance energy production with component preservation
Solution Approach 2:
The system changes operational parameters (power reference values, torque, speed) based on calculated fatigue lifetime consumption rates. By monitoring and adjusting these parameters dynamically, the turbine can operate closer to maximum capacity when components have sufficient remaining life, and reduce load when fatigue consumption accelerates, thereby optimizing both energy production and component lifespan
2Productivity
If wind turbine operates at over-rated power levels, then energy capture is increased, but wear and tear on components increases leading to reduced lifetime
Solution Approach 1:
The system employs feedback mechanisms where fatigue lifetime estimates are continuously calculated based on operational data and used to adjust power reference values. This closed-loop control ensures that over-rating is applied only when beneficial and sustainable, with automatic reduction when fatigue consumption becomes excessive, thus maintaining both high energy capture and component reliability
Solution Approach 2:
The patent calculates and plans future power reference values in advance based on projected fatigue lifetime consumption and component replacement schedules. By anticipating future conditions and constraints, the system can optimize current operation to maximize energy capture while ensuring components are replaced or maintained before failure, preventing reliability degradation
3Productivity
If control schedule is optimized for maximum energy production, then AEP increases, but maintenance frequency increases due to accelerated fatigue
Solution Approach 1:
The system performs preliminary optimization of control schedules by calculating future power reference values and component replacement timing in advance. This proactive approach allows planning maintenance activities during periods of lower energy value or lower wind resource availability, minimizing the impact of maintenance downtime on overall AEP while still allowing aggressive operation during high-value periods
Data Source
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AI summary
Methods and Systems for Generating Wind Turbine Control Schedules A method of generating a control schedule for a wind turbine is provided,, the control schedule indicating how the turbine maximum power level varies over time, the method comprising: determining a value indicative of the current remaining fatigue lifetime of the turbine, or one or more turbine components, based on measured wind turbine site and/or operating data; applying an optimisation function that varies an initial control schedule to determine an optimised control schedule by varying the trade off between energy capture and fatigue life consumed by the turbine or the one or more turbine components until an optimised control schedule is determined, the optimisation including: estimating future fatigue lifetime consumed by the turbine or turbine component over the duration of the varied control schedule based on the current remaining fatigue lifetime and the varied control schedule; and constraining the optimisation of the control schedule according to one or more input constraints; wherein the optimisation further includes varying an initial value for a wind turbine lifetime, and varying an initial value for the number of component replacements, for one or more components, to be performed over the course of the schedule to determine a combination of the number of component replacements for one or more turbine components and a target minimum wind turbine lifetime.