Method for real-time prediction of wind conditions across a wind farm

Patent metadata

Field	Value
Publication number	US-11726232-B2
Application number	US-202218081354-A
Country	US
Kind code	B2
Filing date	Dec 14, 2022
Priority date	Dec 14, 2021
Publication date	Aug 15, 2023
Grant date	Aug 15, 2023

Abstract

A method for real-time prediction of wind conditions across a wind farm comprising a plurality of wind turbines, the wind farm being arranged at a wind farm site, is disclosed. A first library of site specific mean wind flow patterns related to the wind farm site, and a second library of non-site specific turbulence patterns, are provided. Weather data is measured at a plurality of positions within the wind farm site, and based on the measured weather data, a mean wind flow pattern is selected based on the first library and a turbulence pattern is selected based on the second library. A site specific wind flow field across the wind farm site is modelled, based on the selected mean wind flow pattern and the selected turbulence pattern, and wind conditions across the wind farm are predicted, based on the site specific wind flow field.

First claim

The invention claimed is:

1. A method for real-time prediction of wind conditions across a wind farm comprising a plurality of wind turbines, the wind farm being arranged at a wind farm site, the method comprising:
providing a first library of site specific mean wind flow patterns related to the wind farm site;
providing a second library of non-site specific turbulence patterns;
measuring weather data at a plurality of positions within the wind farm site;
based on the measured weather data, selecting a mean wind flow pattern based on the first library and a turbulence pattern based on the second library;
modelling a site specific wind flow field across the wind farm site, based on the selected mean wind flow pattern and the selected turbulence pattern; and
predicting wind conditions across the wind farm, based on the site specific wind flow field.

2. The method of claim 1 , wherein measuring weather data, selecting a mean wind flow pattern and a turbulence pattern, and modelling a site specific wind flow field are performed in real-time or quasi real-time.

3. The method of claim 1 , wherein modelling a site specific wind flow field is further based on wake effects of wind turbines arranged in the wind farm.

4. The method of claim 1 , wherein providing a first library of site specific mean wind flow patterns related to the wind farm site comprises modelling mean wind flow patterns as a function of time of day and/or as a function of time of year, based on historical weather data related to the wind farm site.

5. The method of claim 4 , wherein the step of providing a first library ( 9 ) of site specific mean wind flow patterns further takes known terrain features of the wind farm site into account.

6. The method of claim 1 , wherein providing a second library of non-site specific turbulence patterns comprises modelling turbulence patterns based on general topological features.

7. The method of claim 1 , wherein measuring weather data at a plurality of positions within the wind farm site comprises measuring wind data at a plurality of positions within the wind farm site.

8. The method of claim 1 , wherein selecting a mean wind flow pattern based on the first library comprises the steps of:
comparing the measured weather data to weather data related to the mean wind flow patterns of the first library; and
selecting a mean wind flow pattern which provides the best match between the measured weather data and the weather data related to the mean wind flow patterns.

9. The method of claim 8 , wherein selecting a mean wind flow pattern comprises the steps of:
generating an interpolation between two or more of the mean wind flow patterns of the first library, or an extrapolation of one of the mean wind flow patterns of the first library, based on the step of comparing, thereby obtaining an interpolated or extrapolated mean wind flow pattern; and
selecting the interpolated or extrapolated mean wind flow pattern.

10. The method of claim 1 , wherein selecting a turbulence pattern based on the second library comprises the steps of:
comparing the measured weather data to weather data related to the turbulence patterns of the second library; and
selecting a turbulence pattern which provides the best match between the measured weather data and the weather data related to the turbulence patterns.

11. The method of claim 10 , wherein the step of selecting a turbulence pattern comprises:
generating an interpolation between two or more of the turbulence patterns of the second library, or an extrapolation of one of the turbulence patterns of the second library, based on the step of comparing, thereby obtaining an interpolated or extrapolated turbulence pattern; and
selecting the interpolated or extrapolated turbulence pattern.

12. The method of claim 1 , further comprising updating the first library and/or the second library, based on the measured weather data.

13. The method of claim 1 , further comprising controlling the wind turbines of the wind farm in accordance with the predicted wind conditions across the wind farm.

14. The method of claim 1 , further comprising comparing sensor readings from one or more sensors arranged in the wind farm to the predicted wind conditions, and evaluating reliability of the one or more sensors, based on the comparison.

15. The method of claim 1 , wherein predicting wind conditions across the wind farm, based on the site specific wind flow field, comprises predicting wind conditions across the wind farm during an immediate future time period of 1-10 minutes.

16. A method for real-time prediction of wind conditions across a wind farm comprising a plurality of wind turbines, the wind farm being arranged at a wind farm site, the method comprising:
providing a first library of site specific mean wind flow patterns related to the wind farm site;
providing a second library of non-site specific turbulence patterns;
measuring weather data at a plurality of positions within the wind farm site;
based on the measured weather data, selecting a mean wind flow pattern based on the first library and a turbulence pattern based on the second library;
modelling a site specific wind flow field across the wind farm site, based on the selected mean wind flow pattern and the selected turbulence pattern; and
predicting wind conditions across the wind farm, based on the site specific wind flow field;
wherein:
measuring weather data, selecting the mean wind flow pattern and the turbulence pattern, and modelling the site specific wind flow field are performed in real-time or quasi real-time; and
modelling the site specific wind flow field is further based on wake effects of wind turbines arranged in the wind farm.

Assignees

• Vestas Wind Sys As

Inventors

• Machefaux Ewan
• Andersen Kim Emil
• Ormel Frank
• Bjerning Mogens

Classifications

• G06Q10/04 Primary

  Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202) · CPC title

• G06F30/28

  using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD] · CPC title

• G06Q50/06

  Energy or water supply · CPC title

• G06F2113/06

  Wind turbines or wind farms · CPC title

• G06F2113/08

  Fluids · CPC title