EWEC06 (2006.2.28, Athens)
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EWEC06 (2006.2.28, Athens). Numerical Site Calibration on a Complex Terrain and its Application for Wind Turbine Performance Measurements. Masatoshi FUJINO Daisuke MATSUSHITA Takanori UCHIDA Hikaru MATSUMIYA Masao WATANABE Yoshinori HARA Minori SHIROTA. Toshiyuki SANADA

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Toshiyuki SANADA (Mechanical Engineering Science, Kyushu University, Japan)

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Toshiyuki sanada mechanical engineering science kyushu university japan

EWEC06 (2006.2.28, Athens)

Numerical Site Calibration on a Complex Terrain and its Application for Wind Turbine Performance Measurements

Masatoshi FUJINO

Daisuke MATSUSHITA

Takanori UCHIDA

Hikaru MATSUMIYAMasao WATANABE

Yoshinori HARA

Minori SHIROTA

Toshiyuki SANADA

(Mechanical Engineering Science, Kyushu University, Japan)

Standardization research of wind turbine in Japan

Supported by NEDO (New Energy Development Organization)


Toshiyuki sanada mechanical engineering science kyushu university japan

EWEC06 (2006.2.28, Athens)

Outline 1

A pair of masts

Numerical Site Calibration

Reference meteorological mast

Wind Speed at a wind turbine

Wind speed

CFD (Computational Fluid Dynamics)

Meteorological mast

Fluid Dynamics Lab, Kyushu University


Toshiyuki sanada mechanical engineering science kyushu university japan

EWEC06 (2006.2.28, Athens)

Outline 2

Flow Correction Factor due to Complex Terrain

LES

Prediction of wind speed

GIS

Meteorological mast

Wind Turbine Performance Measurements


Toshiyuki sanada mechanical engineering science kyushu university japan

Introduction

~ Wind Turbine in Japan ~

Renewable energy

1.35% of total electricity supply(2010)

Ratification of Kyoto Protocol

Renewable Portfolio Standard (RPS) Law

Wind power

almost 1/10 of Germany’s !!

March, 2004926 MW

2010 3,000 MW (the official government target)

2030 11,800 MW (the new target of JWPA)

Challenges for Japanese wind turbine development

Complex terrain, Typhoon, Turbulence, Gust, Thunder storm …


Toshiyuki sanada mechanical engineering science kyushu university japan

Introduction

~ Wind Turbine in Japan ~

Wind Turbines in Japan

Complex Terrain

for Japanese wind turbine development

mountain area 73%planes 14%

50% of the people live in plains.

Wind Turbine Performance Measurements at Complex Terrain

for next step…

Prediction of wind power generation


Toshiyuki sanada mechanical engineering science kyushu university japan

Introduction

Performance Measurements

IEC61400-12-1

Example

wind speed at reference mast= wind speed at wind turbine

wind speed not influenced by wind turbine

requirement of high accuracy in measuring wind speed


Toshiyuki sanada mechanical engineering science kyushu university japan

Introduction

Site Calibration Complex Terrain

Flow correction factor b (=the wind speed at the wind turbine location divided by the wind speed at the meteorology mast)

Test site requirements(topographical variations)

・Maximum slope <5%(between 2L and 4L)

・Eliminate the direction > 0.02 in b between neighboring sector

・Each wind direction bin, no larger than 10°

V1=bV2

IEC61400-12-1


Toshiyuki sanada mechanical engineering science kyushu university japan

Introduction

Site Calibration Japan

Wind Turbine Performance Measurements

Imamura et al. (EWEC01)

  • Complex terrain that fails to satisfy the IEC standard

  • Two points correlation analysis (before WT is constructed)

  • Correlation equation using 10miniuts average.

  • Direction with high correlation

  • (eliminate the direction with high turbulent intensity)

After measurements….,

If there is no direction with high correlation?

COST

RISK


Toshiyuki sanada mechanical engineering science kyushu university japan

Objective

  • To propose anumerical site calibration, which employs CFD for wind field simulation over a complex terrain to evaluateflow correction factor.


Toshiyuki sanada mechanical engineering science kyushu university japan

Measurements

Numerical Analysis

Methods

  • To measure the wind speed at reference mast

  • To calculate the flow correction factor b using CFD

  • To correct the wind speed using b

  • To evaluate the wind turbine performance

V1=bV2

V1=bV2


Toshiyuki sanada mechanical engineering science kyushu university japan

Numerical Analysis

RIAM-COMPACT (Uchida & Ohya, 1999, 2003)

Grid scale vortex : Navier-Stokes Eq.

Sub-grid scale vortex : model

LES (Large Eddy Simulation)

Nonlinear, Unsteady simulation !

  • time series analysis

  • correlation

  • turbulent intensity

  • etc…


Toshiyuki sanada mechanical engineering science kyushu university japan

Numerical Analysis


Toshiyuki sanada mechanical engineering science kyushu university japan

Digital Map

Wind turbine performance measurements

Numerical simulation of wind turbine scale

Digital map of wind turbine scale

c.f. GSI map (50m, most commonly used)

GIS (Geographic Information System) technique

aero-photograph

Printed atlas

aero-photograph

CAD data


Toshiyuki sanada mechanical engineering science kyushu university japan

Computational Grid

160 x 160 x 60


Toshiyuki sanada mechanical engineering science kyushu university japan

Test Site ~takashima~

N

topographical variations

fails to satisfy the IEC standard : test site requirement site calibration


Toshiyuki sanada mechanical engineering science kyushu university japan

Measurements

Spatial configuration of WT & mast

N

L=5.13D

mast1: reference mast

mast2: for validity check


Toshiyuki sanada mechanical engineering science kyushu university japan

mast1 mast2

Wind Characteristics

1st, April, 05 ~ 30th, November, 2005

Wind Rose Average Wind Speed Average Turbulent Intensity

[%] [m/s] [%]

N

NW, N, S


Toshiyuki sanada mechanical engineering science kyushu university japan

M1

WT

N

Correction Factor

How to define the flow correction factor b?

Example, North wind

Condition: 5m/s, 10m/s, 15m/s, 10minuts

  • time series of wind speed of each points

z=M1

mast 1

WT


Toshiyuki sanada mechanical engineering science kyushu university japan

Correction Factor

How to define the flow correction factor b?

  • 10 minutes averaged value (corresponding to 10 minute data set)

regression line (minimum mean square method)

correlation coefficient : high

However …

Uncertainly analysis


Toshiyuki sanada mechanical engineering science kyushu university japan

(a)

(b)

Correction Factor

Uncertainly analysis

mast 1

WT

Assumption: bivariate normal distribution

u=N(0, s2): component of variation from average wind speed


Toshiyuki sanada mechanical engineering science kyushu university japan

Correction Factor

How to define the flow correction factor b?

  • confidence interval 95% (±1.97s)

evaluation of correction factor b

error of UWT

In this case,

a=21%

High accuracy in measuring wind speed is required.

The power is approximately proportional to wind speed to the third power.


Toshiyuki sanada mechanical engineering science kyushu university japan

N

NW

Results ~NORTH WEST~

Flow Field

y=WT

y

z

M2

M1

WT

Mast1 & WT: flow smooth

mast2: large Uz components

y=M2


Toshiyuki sanada mechanical engineering science kyushu university japan

N

NW

Results ~NORTH WEST~

Flow Correction Factor

regression analysis

b=1.059

a=0.6%

Good direction for WT performance measurements


Toshiyuki sanada mechanical engineering science kyushu university japan

N

NW

Results ~NORTH WEST~

Validity Check

validity check : mast 1 & mast 2

Measurements (10min data-set)

Calculation

cup vs. cup

over estimation?

y=M2


Toshiyuki sanada mechanical engineering science kyushu university japan

N

N

Results ~NORTH~

Flow Field

Flow Field

M1

M1

WT

WT

z=mast1

z=mast1


Toshiyuki sanada mechanical engineering science kyushu university japan

N

N

Results ~NORTH~

Flow Correction Factor

regression analysis

b=1.2241

a=21%

Poor direction for WT performance measurements


Toshiyuki sanada mechanical engineering science kyushu university japan

N

S

Results ~SOUTH~

Flow Field

Flow Field

M1

WT

y=WT

z=WT

WT


Toshiyuki sanada mechanical engineering science kyushu university japan

N

S

Results ~SOUTH~

Flow Correction Factor

regression analysis

b=1.0844

a=1.0%

Good direction for WT performance measurements


Toshiyuki sanada mechanical engineering science kyushu university japan

Results ~SOUTH~

Validity Check

What happen at the Mast 2 ?

Turbulent Intensity

WT

M2

Siting of Meteorological mast

a=53.0% !!


Toshiyuki sanada mechanical engineering science kyushu university japan

N

NW

Power Performance~ NORTH WEST ~


Toshiyuki sanada mechanical engineering science kyushu university japan

N

N

Power Performance~ NORTH ~


Toshiyuki sanada mechanical engineering science kyushu university japan

N

S

Power Performance~ SOUTH ~


Toshiyuki sanada mechanical engineering science kyushu university japan

Conclusion

  • A site calibration by employing CFD (LES and detail digital map obtained from GIS) is proposed.

  • A numerical site calibration can evaluate directional flow correction factor.

  • A numerical site calibration can be applied to the wind turbine performance measurements if terrain condition and flow direction are carefully chosen.

  • Using numerical simulation, the appropriate direction and position of meteorological mast for site calibration where fluctuation of wind speed is small, can be chosen.


Toshiyuki sanada mechanical engineering science kyushu university japan

For Future

  • Numerical site calibration at other sites. (validity check)

  • Measurements of wind turbine performance at complex terrain

  • (effects of flow distortion, turbulent intensity)

  • (For Japanese wind turbine development, a performance testing of WT at complex terrain is required for prediction of electric power generation)


Toshiyuki sanada mechanical engineering science kyushu university japan

N

N

Results ~NORTH~

Validity Check

validity check : mast 1 & mast 2

Measurements (10min data-set)

Calculation

Measurements: north wind at mast1 = Calculation : north wind into island


Toshiyuki sanada mechanical engineering science kyushu university japan

N

S

Results ~SOUTH~

Validity Check

validity check : mast 1 & mast 2

Measurements (10min data-set)

Calculation

Qualitatively good agreement


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