# US 2021/0277867 A1 · METHOD OF DETERMINING WIND DIRECTION BY MEANS OF A LiDAR SENSOR

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- Number: US 2021/0277867 A1
- Document ID: US20210277867A1
- Status: Published application
- Kind: A1
- Application number: 17/173,103
- Filed: 2021-02-10
- Published: 2021-09-09
- Earliest claimed: 2020-02-10
- Assignees: Ifp Energies Nouvelles
- Applicants: IFP Energies nouvelles
- Inventors: Fabrice GUILLEMIN; Hoai-Nam NGUYEN
- Web page: https://patentgrep.com/patent/US20210277867A1

## CPC

- F03D 7/0204: {for orientation in relation to wind direction}
- F03D 17/00: Monitoring or testing of wind motors, e.g. diagnostics (testing during commissioning of wind motors F03D13/30)
- G01S 17/95: for meteorological use
- F05B 2270/32: Wind speeds
- F05B 2270/321: Wind directions
- F05B 2270/8042: Lidar systems
- G01P 5/26: by measuring the direct influence of the streaming fluid on the properties of a detecting optical wave
- Y02E 10/72: Wind turbines with rotation axis in wind direction
- F03D: WIND MOTORS
- G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- F05B: INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
- G01P: MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT (measuring or recording blood flow A61B5/02, A61B8/06; monitoring speed or deceleration of electrically-propelled vehicles B60L3/00; vehicle lighting systems adapted to indicate speed B60Q1/54; determining position or course in navigation, measuring ground distance in geodesy or surveying G01C; combined measuring devices for measuring two or more variables of movement G01C23/00; measuring velocity of sound G01H; measuring velocity of light G01J7/00; measuring direction or velocity of solid objects by reception or emission of radiowaves or other waves and based on propagation effects, e.g. Doppler effect, propagation time, direction of propagation, G01S; measuring speed of nuclear radiation G01T; measuring acceleration of gravity G01V; {measuring or recording the speed of trains B61L23/00; speed indicators incorporated in motor vehicles B60K35/00; measuring frequency or phase G01R; traffic control G08G})
- Y02E: REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION

## Abstract

The present invention relates to a method of determining the direction of the wind by a LiDAR sensor (2). This method comprises performing measurements by the LiDAR sensor (2), deducing a Gaussian distribution of the longitudinal (u) and transverse (v) components of the wind speed, and determining wind direction (θ) by a spherical cubature approximation method and of the Gaussian distribution of the longitudinal and transverse components of the wind speed.

## Claims

### Claim at position 1

-11. (canceled)

### Claim 12

A method for determining the wind direction by use of a LiDAR sensor arranged on a wind turbine, comprising steps of:
a) performing wind measurements by use of the LiDAR sensor in at least one measurement plane upstream from the wind turbine, the measurement plane being perpendicular to a measurement direction of the LiDAR sensor;
b) determining a Gaussian distribution of longitudinal and transverse components of wind speed by use of the measurements, the longitudinal component corresponding to the measurement direction of LiDAR sensor, and the transverse component corresponding to a direction perpendicular to the measurement direction of LiDAR sensor; and
c) determining in real time the wind direction by use of the determined Gaussian distribution of the longitudinal and transverse components of the wind speed through a spherical cubature approximation method.

### Claim 13 (depends on 12)

A method of determining the wind direction as claimed in claim 12, wherein the Gaussian distribution of the longitudinal and transverse components of the wind speed is determined by use of a wind field estimator.

### Claim 14 (depends on 12)

A method of determining the wind direction as claimed in claim 12, wherein the method further determines a standard deviation of the wind direction.

### Claim 15 (depends on 13)

A method of determining the wind direction as claimed in claim 13, wherein the method further determines a standard deviation of the wind direction.

### Claim 16 (depends on 12)

A method of determining the wind direction as claimed in claim 12, wherein the spherical cubature approximation involves five stochastic realizations from the Gaussian distribution of the longitudinal and transverse components of the wind speed.

### Claim 17 (depends on 13)

A method of determining the wind direction as claimed in claim 13, wherein the spherical cubature approximation involves five stochastic realizations from the Gaussian distribution of the longitudinal and transverse components of the wind speed.

### Claim 18 (depends on 14)

A method of determining the wind direction as claimed in claim 14, wherein the spherical cubature approximation involves five stochastic realizations from the Gaussian distribution of the longitudinal and transverse components of the wind speed.

### Claim 19 (depends on 15)

A method of determining the wind direction as claimed in claim 15, wherein the spherical cubature approximation involves five stochastic realizations from the Gaussian distribution of the longitudinal and transverse components of the wind speed.

### Claim 20 (depends on 12)

A method of determining the wind direction as claimed in claim 12, wherein the wind direction is determined by use of the spherical cubature approximation method by carrying out steps of:
i) determining stochastic realizations of the Gaussian distribution of the longitudinal uj and transverse vj components of the wind speed, with i ranging from −2 to 2, so that:
{
[
u
0
⁡
(
k
)
v
0
⁡
(
k
)
]
⁢
=
[
u
^
⁡
(
k
)
v
^
⁡
(
k
)
]
,
[
u
±
1
⁡
(
k
)
v
±
1
⁡
(
k
)
]
=
[
u
^
⁡
(
k
)
v
^
⁡
(
k
)
]
±
2
⁢
δ
1
⁢
S
1
[
u
±
2
⁡
(
k
)
v
±
2
⁡
(
k
)
]
=
[
u
^
⁡
(
k
)
v
^
⁡
(
k
)
]
±
2
⁢
δ
2
⁢
S
2
,
⁢
⁢
with
⁢
⁢
Σ
=
[
δ
1
2
0
0
δ
2
2
]
,
⁢
P
⁡
(
k
)
=
S
⁢
⁢
Σ
⁢
⁢
S
T
,
⁢
P
⁡
(
k
)
=
δ
1
2
⁢
S
1
⁢
S
1
T
+
δ
2
2
⁢
S
2
⁢
S
2
T
,
û and {circumflex over (v)} being the estimated values of u and v, P(k) being the covariance matrix of the Gaussian distribution, S and Σ being the matrices obtained from the singular value decomposition of covariance matrix P(k), S1 and S2 being the columns of matrix S,
ii) for each stochastic realization j, determining wind direction θj by use of the following equation:
θ
j
⁡
(
k
)
=
arctan
⁡
(
v
j
⁡
(
k
)
u
j
⁡
(
k
)
)
,
and
iii) determining wind direction {circumflex over (θ)} by use of the following equation:
θ
^
⁡
(
k
)
=
∑
j
=
-
2
2
⁢
⁢
w
j
⁢
θ
j
⁡
(
k
)
,
with ωj weightings of the stochastic realizations.

### Claim 21 (depends on 13)

A method of determining the wind direction as claimed in claim 13, wherein the wind direction is determined by use of the spherical cubature approximation method by carrying out steps of:
i) determining stochastic realizations of the Gaussian distribution of the longitudinal uj and transverse vj components of the wind speed, with i ranging from −2 to 2, so that:
{
[
u
0
⁡
(
k
)
v
0
⁡
(
k
)
]
⁢
=
[
u
^
⁡
(
k
)
v
^
⁡
(
k
)
]
,
[
u
±
1
⁡
(
k
)
v
±
1
⁡
(
k
)
]
=
[
u
^
⁡
(
k
)
v
^
⁡
(
k
)
]
±
2
⁢
δ
1
⁢
S
1
[
u
±
2
⁡
(
k
)
v
±
2
⁡
(
k
)
]
=
[
u
^
⁡
(
k
)
v
^
⁡
(
k
)
]
±
2
⁢
δ
2
⁢
S
2
,
⁢
⁢
with
⁢
⁢
Σ
=
[
δ
1
2
0
0
δ
2
2
]
,
⁢
P
⁡
(
k
)
=
S
⁢
⁢
Σ
⁢
⁢
S
T
,
⁢
P
⁡
(
k
)
=
δ
1
2
⁢
S
1
⁢
S
1
T
+
δ
2
2
⁢
S
2
⁢
S
2
T
,
û and {circumflex over (v)} being the estimated values of u and v, P(k) being the covariance matrix of the Gaussian distribution, S and Σ being the matrices obtained from the singular value decomposition of covariance matrix P(k), S1 and S2 being the columns of matrix S,
ii) for each stochastic realization j, determining wind direction θj by use of the following equation:
θ
j
⁡
(
k
)
=
arctan
⁡
(
v
j
⁡
(
k
)
u
j
⁡
(
k
)
)
,
and
iii) determining wind direction {circumflex over (θ)} by use of the following equation:
θ
^
⁡
(
k
)
=
∑
j
=
-
2
2
⁢
⁢
w
j
⁢
θ
j
⁡
(
k
)
,
with ωj weightings of the stochastic realizations.

### Claim 22 (depends on 14)

A method of determining the wind direction as claimed in claim 14, wherein the wind direction is determined by use of the spherical cubature approximation method by carrying out steps of:
i) determining stochastic realizations of the Gaussian distribution of the longitudinal uj and transverse vj components of the wind speed, with i ranging from −2 to 2, so that:
{
[
u
0
⁡
(
k
)
v
0
⁡
(
k
)
]
⁢
=
[
u
^
⁡
(
k
)
v
^
⁡
(
k
)
]
,
[
u
±
1
⁡
(
k
)
v
±
1
⁡
(
k
)
]
=
[
u
^
⁡
(
k
)
v
^
⁡
(
k
)
]
±
2
⁢
δ
1
⁢
S
1
[
u
±
2
⁡
(
k
)
v
±
2
⁡
(
k
)
]
=
[
u
^
⁡
(
k
)
v
^
⁡
(
k
)
]
±
2
⁢
δ
2
⁢
S
2
,
⁢
⁢
with
⁢
⁢
Σ
=
[
δ
1
2
0
0
δ
2
2
]
,
⁢
P
⁡
(
k
)
=
S
⁢
⁢
Σ
⁢
⁢
S
T
,
⁢
P
⁡
(
k
)
=
δ
1
2
⁢
S
1
⁢
S
1
T
+
δ
2
2
⁢
S
2
⁢
S
2
T
,
û and {circumflex over (v)} being the estimated values of u and v, P(k) being the covariance matrix of the Gaussian distribution, S and Σ being the matrices obtained from the singular value decomposition of covariance matrix P(k), S1 and S2 being the columns of matrix S,
ii) for each stochastic realization j, determining wind direction θj by use of the following equation:
θ
j
⁡
(
k
)
=
arctan
⁡
(
v
j
⁡
(
k
)
u
j
⁡
(
k
)
)
,
and
iii) determining wind direction {circumflex over (θ)} by use of the following equation:
θ
^
⁡
(
k
)
=
∑
j
=
-
2
2
⁢
⁢
w
j
⁢
θ
j
⁡
(
k
)
,
with ωj weightings of the stochastic realizations.

### Claim 23 (depends on 15)

A method of determining the wind direction as claimed in claim 15, wherein the wind direction is determined by use of the spherical cubature approximation method by carrying out steps of:
i) determining stochastic realizations of the Gaussian distribution of the longitudinal uj and transverse vj components of the wind speed, with i ranging from −2 to 2, so that:
{
[
u
0
⁡
(
k
)
v
0
⁡
(
k
)
]
⁢
=
[
u
^
⁡
(
k
)
v
^
⁡
(
k
)
]
,
[
u
±
1
⁡
(
k
)
v
±
1
⁡
(
k
)
]
=
[
u
^
⁡
(
k
)
v
^
⁡
(
k
)
]
±
2
⁢
δ
1
⁢
S
1
[
u
±
2
⁡
(
k
)
v
±
2
⁡
(
k
)
]
=
[
u
^
⁡
(
k
)
v
^
⁡
(
k
)
]
±
2
⁢
δ
2
⁢
S
2
,
⁢
⁢
with
⁢
⁢
Σ
=
[
δ
1
2
0
0
δ
2
2
]
,
⁢
P
⁡
(
k
)
=
S
⁢
⁢
Σ
⁢
⁢
S
T
,
⁢
P
⁡
(
k
)
=
δ
1
2
⁢
S
1
⁢
S
1
T
+
δ
2
2
⁢
S
2
⁢
S
2
T
,
û and {circumflex over (v)} being the estimated values of u and v, P(k) being the covariance matrix of the Gaussian distribution, S and Σ being the matrices obtained from the singular value decomposition of covariance matrix P(k), S1 and S2 being the columns of matrix S,
ii) for each stochastic realization j, determining wind direction θj by use of the following equation:
θ
j
⁡
(
k
)
=
arctan
⁡
(
v
j
⁡
(
k
)
u
j
⁡
(
k
)
)
,
and
iii) determining wind direction {circumflex over (θ)} by use of the following equation:
θ
^
⁡
(
k
)
=
∑
j
=
-
2
2
⁢
⁢
w
j
⁢
θ
j
⁡
(
k
)
,
with ωj weightings of the stochastic realizations.

### Claim 24 (depends on 14)

A method of determining the wind direction as claimed in claim 14, wherein a standard deviation {circumflex over (σ)} of the wind direction {circumflex over (θ)} is determined by use of the following equation:
σ
^
⁡
(
k
)
=
∑
j
=
-
2
2
⁢
⁢
w
j
⁡
(
θ
j
⁡
(
k
)
-
θ
^
⁡
(
k
)
)
2
.

### Claim 25 (depends on 15)

A method of determining the wind direction as claimed in claim 15, wherein a standard deviation {circumflex over (σ)} of the wind direction {circumflex over (θ)} is determined by use of the following equation:
σ
^
⁡
(
k
)
=
∑
j
=
-
2
2
⁢
⁢
w
j
⁡
(
θ
j
⁡
(
k
)
-
θ
^
⁡
(
k
)
)
2
.

### Claim 26 (depends on 20)

A method of determining the wind direction as claimed in claim 20, wherein the weightings ωj are defined as follows:
{
w
0
=
1
3
,
⁢
w
j
=
1
6
,
∀
j
=
{
-
2
,
-
1
,
1
,
2
}

### Claim 27 (depends on 12)

A method of controlling a wind turbine equipped with a LiDAR sensor, comprising steps of:
a) determining the wind direction upstream from wind turbine by means of the use as claimed in claim 12, and
b) controlling the wind turbine according to the wind direction upstream from the wind turbine.

### Claim 28 (depends on 12)

A computer program product, comprising code instructions for carrying out the steps of a method as claimed in claim 12, when the program is executed on a processing unit of the LiDAR sensor.

### Claim 29 (depends on 12)

A LiDAR sensor for a wind turbine, comprising a processing unit implementing a method as claimed in claim 12.

### Claim 30 (depends on 29)

A wind turbine, comprising a LiDAR sensor as claimed in claim 29, wherein the LiDAR sensor is on the nacelle of the wind turbine or in a hub of the wind turbine.