Method of determining the vertical profile of the wind speed upstream from a wind turbine equipped with a lidar sensor

Patent metadata

Field	Value
Publication number	US-2020400836-A1
Application number	US-202016906105-A
Country	US
Kind code	A1
Filing date	Jun 19, 2020
Priority date	Jun 19, 2019
Publication date	Dec 24, 2020
Grant date	—

Abstract

The invention relates to a method of determining the vertical profile of the wind speed upstream from a wind turbine (1), wherein wind speed measurements are performed by means of a LiDAR sensor (2), then the exponent α of the power law is determined by means of an unscented Kalman filter and measurements, and this exponent α is applied to the power law in order to determine the vertical wind speed profile.

First claim

1 . A method of determining the vertical profile of the wind speed upstream from a wind turbine, the wind turbine being equipped with a LiDAR sensor facing upstream of the wind turbine, wherein the following steps are carried out:
a) measuring (MES) the wind speed in at least one measurement plane (PM) upstream from the wind turbine at least at two measurement points (PT 1 , PT 2 , PT 3 , PT 4 ) located at different heights by means of the LiDAR sensor, b) constructing a model of the vertical wind speed profile (MOD) by means of a power law of the form:

v
z

v

z
0

=

(

z

z
0

)

α

with vz the longitudinal wind speed at the height z, z0 the reference height, vz0 the longitudinal wind speed at the reference height z0 and α the exponent of the power law,
c) determining the exponent α of the power law by means of an unscented Kalman filter using the wind speed measurements at the two measurement points (PT 1 , PT 2 , PT 3 , PT 4 ), and
d) determining the vertical wind speed profile (PRO) by applying the determined exponent α to the vertical wind speed profile model.

2 . A method of determining the vertical profile of the wind speed as claimed in claim 1 , wherein the unscented Kalman filter is applied to a state model comprising additive noise and multiplicative noise.

3 . A method of determining the vertical profile of the wind speed as claimed in claim 2 , wherein the state model is written:

{

x


(
k
)

=

x


(

k
-
1

)

+

η


(

k
-
1

)

,

y


(
k
)

=

(

v
2



(
k
)

+

ϵ
2



(
k
)

)





(

z
1

z
2

)

x


(
k
)

-

ϵ
1



(
k
)

with x(k)=α(k) the state variable at time k, y(k)=v 1 (k) the output of the state model corresponding to the longitudinal wind speed measured at time k at measurement point 1, η(k−1) the variation of exponent α at time k−1, v 2 (k) the longitudinal wind speed measured at time k at measurement point 2, z1 the height of measurement point 1, z2 the height of measurement point 2, ε1(k) the noise of speed v 1 at time k, and ε2(k) the noise of speed v 2 at time k.

4 . A method of determining the vertical profile of the wind speed as claimed in claim 2 wherein, for applying the Kalman filter, the increasing random variable x a is considered:

x
a



(
k
)

=

[

Assignees

• Ifp Energies Now

Inventors

• Nguyen Hoai-Nam
• Guillemin Fabrice

Classifications

• G01S17/58

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

• Y02E10/72

  Wind turbines with rotation axis in wind direction · CPC title

• G01S7/4802

  using analysis of echo signal for target characterisation; Target signature; Target cross-section · CPC title

• F03D7/00

  Controlling wind motors  (supplying or distributing electrical power H02J, e.g. arrangements for adjusting, eliminating or compensating reactive power in networks H02J3/18; controlling electric generators H02P, e.g. arrangements for controlling electric generators for the purpose of obtaining a desired output H02P9/00) · CPC title

• F05B2270/32

  Wind speeds · CPC title