Method and system for evaluating effective turbulence intensity in wind farm

By introducing the chi-square test into the turbulence intensity assessment, the distribution type of wind farm turbulence data is determined, and the envelope value is used to handle unsatisfactory distributions. This solves the problems of insufficient accuracy and high redundancy in existing technologies, and achieves a more efficient and accurate turbulence intensity assessment.

WO2026025576A1 Publication Date: 2026-02-05CRRC WIND POWER(SHANDONG) CO LTD
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Patent Information

Application Number
PCT/CN2024/114852
Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
Priority Date
2024-07-30
Filing Date
2024-08-27
Publication Date
2026-02-05

AI Technical Summary

Technical Problem

Existing technologies are not accurate enough in assessing turbulence intensity, especially when the Weibull distribution is not met. They have low calculation accuracy, high redundancy, complex operation procedures, and poor applicability.

Method used

By acquiring wind speed time-series data from wind farms, the chi-square independence test is used to determine whether the turbulence data conforms to a normal, log-normal, or Weibull distribution. Based on the test results, the turbulence probability density function is determined, the effective turbulence intensity is calculated, and the envelope value is used to handle cases where the distribution is not met, thereby improving the accuracy of the calculation to closely approximate the actual distribution.

Benefits of technology

It improves the accuracy of turbulence intensity assessment, reduces redundancy, increases computational efficiency, has a wider range of applications, and simplifies the operation process.

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Abstract

The present invention relates to the technical field of turbulence intensity evaluation. Provided are a method and system for evaluating the effective turbulence intensity in a wind farm. The method comprises: acquiring wind speed time series data of a wind farm, and on the basis of the wind speed time series data of the wind farm, obtaining a wind frequency matrix and a turbulence matrix at a target position; acquiring wind-frequency discrete probability density functions for distributions of different wind direction sectors; respectively acquiring environmental turbulence intensities under a normal distribution, a log-normal distribution and a Weibull distribution; performing a chi-square test of independence on an observed frequency and an expected frequency in each turbulence bin interval at each wind speed; on the basis of the results of chi-square tests of independence, using the environmental turbulence intensities under the corresponding distributions to determine turbulence probability density functions; and on the basis of the turbulence probability density functions and the wind-frequency discrete probability density functions, obtaining an effective turbulence intensity. The present invention can improve the evaluation accuracy of effective turbulence intensity.
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