Method for acquiring and modelling an incident wind field by means of a LiDAR sensor

Patent metadata

Field	Value
Publication number	US-11248585-B2
Application number	US-201816621450-A
Country	US
Kind code	B2
Filing date	Jun 20, 2018
Priority date	Jun 21, 2017
Publication date	Feb 15, 2022
Grant date	Feb 15, 2022

Abstract

The invention relates to a method for acquisition and modelling of an incident wind field by a LiDAR sensor. Acquisition and modelling include a step of estimating the wind amplitudes and directions for a set of discretized points, and a step of incident wind field reconstruction in three dimensions and in real time. The invention also relates to a method of controlling and/or monitoring a wind turbine equipped with such a LiDAR sensor from the incident wind field reconstructed in three dimensions and in real time.

First claim

The invention claimed is:

1. A method for incident wind field acquisition and modelling by a LiDAR sensor in a space located upstream from the LiDAR sensor, wherein the method comprises steps of:
a) gridding the space located upstream from the LiDAR sensor where gridding of the space is carried out with a set of discretized points positioned in a predetermined three-dimensional grid comprised of a set of cells made up of estimation points and measurement points;
b) measuring the amplitude and direction of the wind at the different measurement points located in the space located upstream and positioned at least at two distances from the LiDAR sensor, along at least three measurement axes;
c) estimating the wind amplitude and direction at any time on all of the estimation points by optimization using a weighted recursive least-squares method of a cost function that uses at least data from measurement points, wind speed spatial coherence data, wind speed temporal coherence data, and data qualifying a quality of the measurements performed at the measurement points; and
d) reconstructing, in real time and in a predetermined coordinate system, the incident wind field in three dimensions (3D) from the estimated and measured wind amplitudes and directions for each point of the grid; and wherein
measurement m of amplitude and direction of the wind at a measurement point is given by a relationship expressed by:
m j,x ( k )= a j v j,x ( k )+ b j v j,y ( k )+ c j v j,z ( k )

where v j,x (k), v j,y (k), v j,z (k) are values of the wind speed projected onto a given coordinate system x, y, z at an initial time (k), and a j , b j , c j with j=0, 1, 2, 3, 4 are measurement coefficients that are expressed as:

{

a
j

=

cos
⁡

(

θ
j

)

,

b
j

=

sin
⁡

(

θ
j

)

⁢

cos
⁡

(

φ
j

)

,

c
j

=

sin
⁡

(

θ
j

)

⁢

sin
⁡

(

φ
j

)

where θj,φj are zenith and azimuth of the measurement axis respectively in a spherical coordinate system.

2. A method as claimed in claim 1 , wherein cost function J at any time (t) is written as follows:

J
⁡

(
t
)

=

(

ω
⁡

(
0
)

-

ω
^

⁡

(
0
)

)

T

⁢

P
0

-
1

⁡

(

ω
⁡

(
0
)

-

ω
^

⁡

(
0
)

)

+

∑

j
=
1

t

⁢

(

Assignees

• Ifp Energies Now

Inventors

• Nguyen Hoai-Nam
• Guillemin Fabrice

Classifications

• F05B2270/8042

  Lidar systems · CPC title

• F03D7/045 Primary

  with model-based controls · CPC title

• G01S17/95 Primary

  for meteorological use · CPC title

• G01S17/58

  Velocity or trajectory determination systems; Sense-of-movement determination systems · CPC title

• F05B2270/404

  active, predictive, or anticipative · CPC title