Wind Speed Deviation Correction for Wind Farm Power Prediction
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Solution Overview
Problem
Existing fluid models used for wind speed calculations in wind farms, especially in complex terrain and meteorological conditions, result in significant deviations, leading to economic losses due to inaccurate power generation predictions.
Innovation Solution
A correction method and apparatus that establish wind speed deviation matrices and a correction model library based on relationships between wind speed deviations and influence factors, allowing for the determination of relevant parameters and correction of predicted wind speeds in target wind farms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing fluid models (WT, Windsim, WAsP) are used for wind speed calculation, then the calculation process is simple and fast, but the wind speed prediction accuracy deteriorates significantly in complex terrain and meteorological conditions
Solution Approach 1:
The patent introduces an equivalent factor as an intermediary element that bridges the gap between simple fluid models and complex terrain effects. The equivalent factor synthesizes multiple influence factors (terrain complexity, meteorological conditions, wind direction) into a single correction parameter that can be applied to existing fluid models without fundamentally changing their structure, thus improving accuracy while maintaining relative simplicity
Solution Approach 2:
The patent transforms complex terrain and meteorological conditions into quantifiable influence factors that modify the equivalent factor. By changing parameters such as terrain complexity index, wind direction range, and meteorological condition codes into numerical values that affect the equivalent factor calculation, the system adapts the fluid model outputs to match actual conditions without requiring complex new models
2Productivity
If fluid models are applied to wind farms in complex terrain areas, then the deployment is fast, but the economic benefits deteriorate due to large deviations in power generation prediction
Solution Approach 1:
The patent performs preliminary classification of terrain and meteorological conditions before wind speed calculation. By pre-defining influence factors such as terrain complexity indices and meteorological condition categories, the system prepares correction parameters in advance that can be quickly applied during the assessment process, maintaining fast deployment while improving prediction reliability
Solution Approach 2:
The patent uses parameter changes to adjust predictions based on terrain and meteorological conditions. By converting qualitative conditions (e.g., 'complex terrain', 'unstable meteorology') into quantitative influence factors that modify the equivalent factor, the system maintains computational efficiency while significantly improving the reliability of power generation predictions
Data Source
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AI summary
The present invention relates to a correction method for a power generation amount of a wind farm, performed by a calculation apparatus, the correction method comprising establishing a wind speed deviation matrix of a plurality of existing wind farms respectively, where a wind speed deviation represents a difference between a predicted wind speed and a measured wind speed of a target anemometer tower of the existing wind farm, establishing a wind speed deviation correction model library based on the wind speed deviation matrixes of the plurality of existing wind farms, where the wind speed deviation correction model library comprises a plurality of wind speed deviation correction models corresponding to the existing wind farms, and the wind speed deviation correction model represents a relationship between the wind speed deviation and an equivalent factor of the existing wind farm, determining relevant parameters of the target wind farm, determining a matched wind speed deviation correction model in the wind speed deviation correction model library based on the relevant parameters, and correcting the predicted wind speed of the target wind farm based on the determined wind speed deviation correction model, and calculating a corrected power generation amount based on the corrected predicted wind speed.