Wind Farm Dispatch Controller Using Moving Averages
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Solution Overview
Problem
Wind farms face challenges in controlling average frequency variations in power dispatch intervals, leading to unnecessary complex controls and revenue loss due to the use of instantaneous power dispatch control methodologies.
Innovation Solution
A system and method that include identifying a dispatch interval, determining observation and control time intervals, computing moving averages of farm power and grid frequency, and determining a farm power set point based on a predefined operating model to regulate wind turbine operations and optimize revenue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If instantaneous power dispatch control methodology is used, then grid frequency control responsiveness is improved, but control complexity and revenue loss increase
Solution Approach 1:
The system performs preliminary actions by computing moving averages of farm power and grid frequency over observation time intervals before implementing control actions. This allows the system to anticipate frequency deviations and prepare appropriate control responses in advance, improving responsiveness while avoiding reactive complexity
Solution Approach 2:
The patent introduces moving averages as an intermediary between instantaneous power measurements and control decisions. By using smoothed representations of farm power and grid frequency through moving averages, the system filters out high-frequency noise and unnecessary variations, enabling simpler yet effective control actions that maintain grid frequency stability
2Reliability
If instantaneous power dispatch control is applied, then frequency control capability is improved, but revenue generation deteriorates
Solution Approach 1:
The system computes moving averages and determines optimal farm power set points in advance during observation time intervals, allowing wind farm operators to plan power dispatch strategies that maintain frequency control capability while optimizing revenue based on predetermined operating revenue models
Solution Approach 2:
The patent implements a feedback mechanism where the system continuously monitors grid frequency and farm power, compares actual values with moving averages, and adjusts farm power set points accordingly. This closed-loop control ensures frequency stability is maintained while minimizing unnecessary control actions that would reduce revenue
3Device complexity
If moving average control is used, then control simplicity and revenue are improved, but frequency control precision may deteriorate
Solution Approach 1:
The system dynamically adjusts the balance between simplicity and precision by using moving averages with configurable time intervals. The observation time interval and control time interval can be optimized based on grid conditions, allowing the system to maintain frequency control precision while keeping control logic simple through adaptive parameter adjustment
Solution Approach 2:
The patent changes the parameter representation from instantaneous values to moving average values, fundamentally altering how frequency and power are measured and controlled. This parameter transformation simplifies the control logic while maintaining sufficient precision for grid frequency control by filtering out insignificant variations
Data Source
AI summary
A method is provided. The method includes identifying a dispatch interval for dispatching power from a wind farm, determining an observation time interval and a control time interval in the dispatch interval, computing a farm power moving average of the power of the wind farm, computing a grid frequency moving average of a grid frequency, determining a farm power set point based on a predefined wind farm operating model using the farm power moving average and the grid frequency moving average, controlling one or more wind turbines in the wind farm during the control time interval based on the farm power set point to regulate a farm-level dispatch power.