ArticlePDF Available

Long-Term Statistical Analysis of Global Wind Resources Using Reanalysis Data

September 2018
Journal of Wind Energy 9(3):19-24

DOI:10.33519/kwea.2018.9.3.003

Authors:

Hyun-Goo Kim

Korea Institute of Energy Research

Jin-Young Kim

Korea Institute of Energy Research

Third-generation reanalysis data such as CFSR, ERA-Interim, and MERRA, which have improved spatial resolution and accuracy by assimilating satellite observation data, are widely used for the long-term correction of wind resource assessments. However, there is no obvious criterion for the selection of datasets, and the reported accuracy from actual application cases are all different. In this study, we provide basic information for estimating the uncertainty of reanalysis data selection by reviewing the characteristics of each dataset with a quantitative comparison of three kinds of reanalysis data. The wind speed and wind power density showed significant differences between the reanalysis data, but there was relatively little difference in the Weibull shape factor, which defines wind speed distribution. It was found that wind speed distribution in a low latitude band follows normal distribution rather than a Weibull shape. In conclusion, substantial uncertainty is expected depending on the reanalysis data, and further comparison analysis to establish its application guideline is anticipated.

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풍력에너지저널 : 제9권, 제3호, 2018

논문

풍력에너지저널

제9권, 제3호, 2018

pp. 19~24

재해석자료를 이용한 전지구 풍력자원의 장기간 통계분석 1)

김현구*․김진영**․김하양***

Long-Term Statistical Analysis of Global Wind Resources

Using Reanalysis Data

Hyun-Goo Kim*, Jin-Young Kim**, Ha-Yang Kim***

Key Words : Wind resource assessment (

풍력자원평가

), Reanalysis data (

재해석자료

), CFSR (Climate Forecast

System Reanalysis), ERA-Interim (European Reanalysis-Interim), MERRA (Modern Era Reanalysis for

Research and Applications)

ABSTRACT

Third-generation reanalysis data such as CFSR, ERA-Interim, and MERRA, which have improved

spatial resolution and accuracy by assimilating satellite observation data, are widely used for the

long-term correction of wind resource assessments. However, there is no obvious criterion for the

selection of datasets, and the reported accuracy from actual application cases are all different. In this

study, we provide basic information for estimating the uncertainty of reanalysis data selection by

reviewing the characteristics of each dataset with a quantitative comparison of three kinds of reanalysis

data. The wind speed and wind power density showed significant differences between the reanalysis

data, but there was relatively little difference in the Weibull shape factor, which defines wind speed

distribution. It was found that wind speed distribution in a low latitude band follows normal distribution

rather than a Weibull shape. In conclusion, substantial uncertainty is expected depending on the

reanalysis data, and further comparison analysis to establish its application guideline is anticipated.

1. 서 론

풍력발전사업은 사업초기에 풍력자원평가 (WRA;

* 한국에너지기술연구원 , 신재생에너지자원 ·정책센터

(교신저자 )

** 한국에너지기술연구원 , 신재생에너지자원 ·정책센터

*** 한국에너지기술연구원 , 신재생에너지자원 ·정책센터

아주대학교 , 에너지경제학과 대학원

E-mail : hyungoo@kier.re.kr

Received : June 22, 2018, Revised : August 21, 2018

Accepted : August 21, 2018

Wind Resource Assessment) 를 수행하여 연간에너지

생산량에 따른 수익과 풍력발전소의 건설비용 및 유지

보수를 위한 지출을 예측한 후 경제성 있다고 판단될

경우 사업추진을 결정한다 . 일반적으로 풍력발전사업

에서 가장 큰 사업위험은 20

∼

30년을 운영하여야 할

대규모 투자사업의 수익예측, 즉 풍력자원평가이다 . 특

히 단기간의 실측자료로 장기간의 풍력자원을 예측함

에 따른 불확도를 어떻게 낮출 수 있는지가 관건이다.

풍력자원평가를 위한 기상탑(meteorological tower)

측정을 장기간 수행하기는 현실적으로 어렵기 때문에

통상 MCP(Measure-Correlate-Predict) 방법을 이용하

여 단기간 실측자료와 장기간 참조자료 간의 상관관계

김현구 ․김진영 ․김하양

풍력에너지저널 : 제9권, 제3호, 2018

Name Source Time

Range Assimilation Model

Resolution Model Output

Resolution

Publicly

Available

Dataset

Resolution

Dataset Output Times and

Time Averaging

NCEP

CFSR NCEP 1979-

present 3D-VAR T382 L64 0.5 x 0.5 and

2.5 x 2.5 0.5 x 0.5 and

2.5 x 2.5 Hourly, 4 times daily

ECMWF

ERA

Interim ECMWF 1979-

present 4D-VAR

TL255L60

and N128

reduced

Gaussian

TL255L60 and

N128 reduced

Gaussian

(

∼

79km

globally)

User defined,

down to 0.75 x

0.75

3-hourly for most surface

fields; 6-hourly for upper-air

fields

Monthly averages of daily

means, and of 6-hourly fields

NASA

MERRA NASA 1979-

present

3D-VAR,

with

incremental

update

2/3 lon x

1/2 lat

deg; 72

sigma

levels

(

∼

55km)

2/3 lon x 1/2

lat deg 3D

Analysis and

2D variables;

1.25 deg 3D

Diagnostics;

72 model

levels and 42

pressure levels

2/3 lon x 1/2

lat deg 3D

Analysis and

2D variables;

1.25 deg 3D

Diagnostics;

72 model

levels and 42

pressure levels

2D Diagnostics - 1 hourly avg,

centered at half hour; 3D

Diagnostics - 3 hourly avg,

centered at 01:30, 04:30 ... 22:30;

3d Analysis - Instantaneous 6

hourly; 2d Diagnostics, Monthly

mean diurnal average; Monthly

means for all collections; daily

averages processed at servers

on-the-fly

Table 1 Comparison of the 3rd generation reanalysis data (Source: https://reanalyses.org/atmosphere/comparison-table)

로부터 장기간 보정(long-term correction) 을 한다.

최근에는 장기간 참조자료로서 재해석자료를 많이

사용하는 추세이다 [1]. 특히 CFSR, ERA-Interim, 그

리고 MERRA 등 제3세대 재해석자료는 이전 세대에

비하여 공간해상도 및 정확도가 월등히 향상되었을 뿐

아니라 모든 자료가 무료로 공개되고 있다.

Eichelberger et al.이 35지점의 고층기상탑 측정결

과를 이용하여 제3세대 재해석자료를 평가한 바에 따

르면 CFSR과 ERA-Interim 이 MERRA 보다 우수한

것으로 나타났다 [2]. (CFSR & ERA-Interim R2=0.54,

MERRA R2=0.46) Brower et al.이 전세계 37지점의

고층기상탑 측정결과를 이용하여 수행한 비교연구에서

는 CFSR 이 가장 우수한 것으로 나타났다 [3]. (CFSR

R2=0.74, ERA-Interim R2=0.73, MERRA R2=0.66) 한

편 Kim et al.이 한반도 해역에 대해 재해석자료를 평

가한 연구결과에서는 MERRA와 CFSR이 같은 수준의

정확도를 보였다 [4]. (MERRA & CFSR R2=0.63,

ERA-Interim R2=0.61)

재해석자료를 풍력자원평가에 활용하기 위하여 고

층기상탑 측정자료와 비교한 선행연구를 살펴보면 특

정 재해석자료가 월등히 우수한 성능을 보이지는 않았

지만 풍력자원평가에 있어서 무시할 수 없는 수준의

유의미한 차이를 나타내는 것으로 확인되었다 . 즉, 아

직까지 풍력자원평가를 위해 어떤 재해석자료를 선정

해야 할지에 대한 명확한 가이드라인이 없는 실정이다.

본 연구는 3세대 전지구 재해석자료를 풍력자원평

가에 활용함에 앞서 자료의 특성을 체계적으로 파악하

기 위하여 CFSR, ERA-Interim, MERRA 에 대한 통계

분석 및 비교분석을 수행하였다 .

2. 재해석자료

재해석 (reanalysis) 이란 매 6

∼

12시간 간격으로 라디

오존데 (radiosonde), 부이(buoy), 항공기, 선박 등 다양

한 경로로 획득되는 7

∼

9백만 관측자료를 불변성 자료

동화구조(invariant data assimilation structure) 및 수

치

기상모

델

에 통

합

적으로 반영하여 체계적이

며

일관성

있는 전지구 장기간의 기상자료를 재생산하는

접

근방

식

을

말

한다 [5].

1990년대에 미

국

National Center for Atmospheric

Research(NCAR)/National Centers for Environmental

Prediction(NCEP) 에서 생산

된

전지구 재해석자료를 제

1세대라고 한다면 [6], 2000년대에

들

어서

몇

가지 문

제점을 수정하고 동일한 격자

망

에서

물

리과정의 모수

화를 보

완

하여 제2세대 재해석자료가 생산되었다 [7].

2010년대에는 인공위성자료를 활용하여 시공간 해상도

가 월등하게 향상

된

제3세대 재해석자료인 CFSR,

ERA-Interim, MERRA, MERRA-2 등이 개발되었다 .

재해석자료를 이용한 전지구 풍력자원의 장기간 통계분석

풍력에너지저널 : 제9권, 제3호, 2018

Fig. 1 Wind speed map at 50 m height (left: spatial distribution, right: zonally averaged profile along latitude)

Fig. 2 Wind power density map at 50 m height (left: spatial distribution, right: zonally averaged profile along latitude)

Fig. 3 Weibull shape factor map at 50 m height (left: spatial distribution, right: zonally averaged profile along latitude)

2.1 CFSR

CFSR(Climate Forecast System Reanalysis, http://

rda.ucar.edu/pub/cfsr.html) 은 MERRA와 동일한 기상

자료 및 해석모

델

에 기반하

며

, 미

국

NCEP 의 고해상도

전지구 대기-해양-지

표

면-

빙

하 연동 기후예측체계

(Climate Forecast System)에 의해 생산

된

다 [8].

2.2 ERA-Interim

ERA-Interim(European Reanalysis-Interim, https://

www.ecmwf.int/en/forecasts/datasets/archive-dataset

s/reanalysis-datasets/era-interim) 은 유

럽

연

합

ECMWF

(European Center for Medium-Range Weather Forecasts)

재해석자료 시리

즈 중

ERA-15, ERA-40에 이어 차세

김현구 ․김진영 ․김하양

풍력에너지저널 : 제9권, 제3호, 2018

대 재해석자료를 생산하기 위한 전단계로 생산되었다 .

ERA-Interim 은 유

럽

연

합

ECMWF 의 통

합

예보모

델

(Integrated Forecast Model)을 기반으로 12시간 간격

의 4차원 변분 자료동화(4D-Var) 와 위성

복

사자료

(satellite radiance data) 편차의 적

응

성 예측모

듈

(VarBC) 을 적용하고 있다 [9].

2.3 MERRA

MERRA(Modern Era Reanalysis for Research and

Applicationsm http://gmao.gsfc.nasa.gov/merra/) 는 인

공위성 시대를 위한 미

국

NASA 의 재해석자료로 ,

NASA GMAO(GSFC Global Modeling Assimilation

Office)에서 생산하는 최

신

의 GEOS-5(Goddard Earth

Observing System Data Assimilation System v5)를

사용하여 2008년부터 정

식

자료생산을 개시하였다 .

MERRA는

광범

위한 기상 및 기후 시간

척

도를 가지는

수문

학

적

주

기(hydrological cycle)의 역사적 분석에

집

중

하고 있으

며

, 기존 재해석자료에 비하여 시공간 해

상도가 획기적으로 향상되었을 뿐 아니라 우수한

토

지

피복

모

델링

을 제공하는 것으로 평가

된

다 [10].

Table 1은 제3세대 재해석자료 3

종

의 규격을 비교

한 것으로 , 시간해상도는 MERRA와 CFSR은 1시간

간격

임

에 비하여 ERA-Interim 은 3시간 간격이

며

, 공

간해상도는 CFSR은 0.5

x 0.5

, MERRA은 0.67

0.5

, ERA-Interim 은 0.75

x 0.75

° 순

서이다 .

3. 전지구 풍력자원평가

본 연구에서는 1979년부터 2014년까지

총

36년간의

자료기간에 해

당

하는 방대한 양의 전지구 재해석자료

종

의 통계분석을 위해 KIER-Reanalysis TM를 사용하

였다. KIER-Reanalysis TM는 한

국

에너지기

술

연구원에

서 개발한 MatLab 기반의 분석

프

로그

램

으로, 전지구

격자

망

에서 연직층

별

로 정의

된

기상

요

소를 1시간

또

는

3시간 간격의 시계

열

자료

형식

의 데이터

베

이

스

로 구성

하고, 사용자의

요

구에 따라 설정

된

분석기간에 대해

격자점에서의 통계량을 산출한 후 그 결과를 출력하

거

나 가시화한다 .

Fig. 1은 36년간의 전지구 평

균

풍

속

분

포

도이다 .

잘

알려

진 바와 같이 지구의 위도에 따른 풍

속

차가 분명

하게

난

다. 우측의 그

래프

에는 동위도에 대해 재해석

자료

별

평

균

화

된

풍

속

(선 그

래프

)과 함

께

재해석자료

간 차이를 비

율

로(

막

대 그

래프

) 도시하였는데 , 전 위도

구간에서 9

정도의 차이가 확인

된

다.

Fig. 2는 전지구 풍력

밀

도(wind power density) 분

포

도이다 . 우측의 동위도 평

균값

을 보면, 풍력

밀

도는

풍

속

의 세제

곱

에 비

례

하기 때문에 재해석자료 간의 차

이는 24

로

크

게

증폭됨

을

알

수 있다.

Fig. 3은 전지구 와이

블 형

상계수 (Weibull shape

factor) 분

포

도로, 적도를

중심

으로

저

위도

밴

드를 따

라

형

성

된 저

풍

속

대에서는 특이하게

형

상계수

값

이

높

은 영역이 나타

난

다. 그 이유를 확인하기 위하여 해

당

영역의 대

표

지점에 대한 풍

속

분

포

를 Fig. 4에 제시하

였는데 , 그 분

포형

상은 와이

블

분

포

보다는 정규분

포

를

가지기 때문에 매우 큰

형

상계수로 산정되었

음

을 확인

할 수 있다. 단, 재해석자료에 따른 동위도 구간

별

와

이

블 형

상계수 평

균값

의 차이는 4

이내로 나타났는

데, 이는 풍

속

과 풍력

밀

도에 비해 재해석자료간 차이

가 매우

작

은 특성을 보였다.

일반적으로 지

형

고도와 풍

속

은 비

례

관계에 있다

[11]. 재해석자료 생산체계에 따른 지

형

고도와 풍

속

의

산

포

도를 Fig. 5에 도시하였으

며

, 이로부터 재해석자료

생산체계가 지

형효

과를 반영함에 있어서 유의한 차이

가 있

음

을 확인할 수 있다. 즉, CFSR과 MERRA 는 지

형

고도의

증

가에 따른 풍

속

의

증

가경향이 유사하게 나

타

난

반면 ERA-Interim 은 상대적으로 공간해상도가

낮아서 지

형

고도와 풍

속

의 상관성이 상대적으로 낮게

나타나고 있다.

Fig. 6은 전지구 영역에서 풍

속

의 통계분

포

를 비교

한 그

래프

이다. 앞서 분석한 바와 같이 재해석자료간

에 유의한 차이가 나타

난

다. 즉, CFSR은 5 m/s의

저

풍

속

구간의

빈

도가

높

은 반면 MERRA 는 7 m/s 구간의

빈

도가

높

게 나타났다 .

막

대 그

래프

로 도시한 재해석

자료간의 차이를 보면 4

∼

5 m/s 구간과 7 m/s에서 가

장 큰 차이가 나타나고 있다.

Fig. 7은 전지구 영역에서 와이

블 형

상계수의 통계

분

포

를 나타

낸

다. 풍

속

의 통계분

포

와는 다르게 재해석

자료 간의 차이는 최대 6

이내로 ,

거

의 유사한 통계

분

포

를

갖

는다.

주

지하자면 Fig. 3의 동위도 영역

별

와

이

블 형

상계수의 평

균값

에 대한 고

찰

결과와 동일하다.

Fig. 8은 전지구 영역에 대한 평

균

풍

속

의 장기간 경년

변화를 비교한 그

래프

이다. 인공위성자료가 동화되기 시

작

한 2010년도 이후 CFSR과 MERRA는 유사한 변동특

성을 보이

며

, 이는 Fig. 5에서 고

찰

한 바와도 동일하다 .

재해석자료를 이용한 전지구 풍력자원의 장기간 통계분석

풍력에너지저널 : 제9권, 제3호, 2018

Fig. 6 Distribution of wind speed by reanalysis data

Fig. 7 Weibull distribution of wind speed by reanalysis data

Fig. 8 Wind speed anomaly for 1979

∼

2014 by reanalysis data

Fig. 4 Weibull distribution of wind speed (7.5°S, 114°W)

(a) CFSR

(b) ERA-Interim

Fig. 5 Scatter plots of terrain elevation versus wind speed

4. 결 론

본 연구에서는 풍력자원평가

중

장기간 보정에 사

용되고 있는 제3세대 전지구 재해석자료 3

종

, 즉

CFSR, ERA-Interim, MERRA 의 정량적 비교평가를

수행하였다 .

김현구 ․김진영 ․김하양

풍력에너지저널 : 제9권, 제3호, 2018

그 결과, 재해석자료의 기초적인 차이점을 확인함으

로

써

풍력자원평가시 재해석자료 선

택

에 따른 불확도

의 추정이 가능할 것으로 기대

된

다.

본 연구의 결

론

을 정리하면 다

음

과 같다.

(1) 풍

속

, 풍력

밀

도의 통계분

포

와 위도에 따른 평

균

값

은 재해석자료 간에 유의한 차이가 나타났다 .

그

러

나 풍

속

분

포

에 대한 와이

블 형

상계수는 4

수준의

작

은 차이만 나타났다. 이는 재해석

자료 간의 차이가 자료생산의 체계적인 오차라

기보다는 자료동화를 위한 기상변수의 설정에

있어서의 차이에 기인한 것으로 추정되

며

, 보다

다

각

도의 비교

검토

가

필요

한 부분이다.

(2) 지

형

고도와 풍

속

의 상관도 비교분석을 통하여

CFSR 과 MERRA 는 지

형

고도의 상

승

에 따라

풍

속

이

증

가하는 동일한 경향을 보였으

며

, 전지

구 평

균

풍

속

의 경년변화에서도 인공위성자료가

동화되기 시

작

한 2010년 이후 매우 유사한

형

태

를 보였다 . 이는

두

재해석자료가 미

국

NCEP 의 생산체계를 사용하는 동

질

적인 재해석

자료인 반면 ERA-Interim 은 유

럽

연

합

ECMWF 의 생산체계를 사용하기 때문에 발생

한 체계적인 차이인 것으로 추정

된

다.

후기

본 연구는 한

국

에너지기

술

연구원의

주요

사업을 재

원으로 수행한 연구과제의 결과

입

니다. (B8-2424-02)

참고문헌

[1] Kim, H.-G., Kang,

.-H.,

un, C.-

., and

ang, M.-S., 2013,

“

Long-Term Wind Resource

Assessment of Shinan-gun Bigeum-do Using

the Wind Farm SCADA Data and Reanalysis

Data,

" J

. of Wind Engineering Institute of

Korea, Vol. 17, No. 4, pp. 127

∼

132 (in Korean).

[2] Eichelberger, S., Stoelinga, M., and McCaa,

2013,

“

Performance of New Reanalysis Data

Sets for Estimating the Temporal and Spatial

Variability of Wind Resource,

European Wind

Energy Conference 2013, Vienna, Austria.

[3] Brower, M.C., Barton, M.S., Lled

, L., and

Dubois,

., 2013, A Study of Wind Speed

Variability Using Global Reanalysis Data,

Technical Report, AWS Truepower, USA, p. 12

[4] Kim, H.-G., Kim,

., and Kang,

.-H., 2018,

“

Comparative Evaluation of the Third-Generation

Reanalysis Data for Wind Resource Assessment

of the Southwestern Offshore in South Korea,

Atmosphere, Vol. 9, No. 73.

[5] Kim, H.-G.,

ang, M.-S., and Ryu, K.-W., 2013,

“

Wind Resource Assessment on the Western

Offshore of Korea Using MERRA Reanalysis

Data,

" J

ournal of Wind Energy, Vol. 4, No. 1,

pp. 39

∼

45 (in Korean).

[6] Kalnay, E., Kanamitsu, M., Kistler, R., Collins,

W., Deaven, and D., Gandin, L., 1996,

“

The

NCEP/NCAR 40-

ear Reanalysis Pro

ect,

Bull.

Amer. Meteor. Soc., Vol. 77, pp. 437

∼

471.

[7] Kanamitsu, M., Ebisu

aki, W., Woollen,

ang, S.K., Hnilo,

., Fiorino, M., and Potter,

G.L., 2002,

“

NCEP

–

DOE AMIP-II Reanalysis(R-2),

Bull. Amer. Meteor. Soc., Vol. 83, pp. 1631

∼

1643.

[8] Saha, S., Moorthi, S., Pan, H.L., Wu,

., Wang,

., Nadiga, S., Tripp, P., and Kistler, R., 2010,

“

The NCEP Climate Forecast System

Reanalysis,

Bull. Amer. Meteor. Soc., Vol. 91,

pp. 1015

∼

1057.

[9] Dee, D.P., Uppala, S.M., Simmons, A.

Berrisford, P., and Poli, P., 2011,

“

The

ERA-Interim Reanalysis: Configuration and

Performance of the Data Assimilation System,

.R. Meteorol. Soc., Vol. 137. pp. 553

∼

597

[10] Rienecker, M.M., Suare

, M.

., Gelaro, R.,

Todling, R., and Bacmeister,

., 2011,

“

MERRA:

NASA

’

s Modern-Era Retrospective Analysis

for Research & Applications,

" J

. Climate, Vol.

24, pp. 3624

∼

3648.

[11] Kim, H.-G., Kang,

.-H., and

un, C.-

2015,

“

Comparative Analysis on Commercial

Wind Resource Maps of South Korea,

" J

. of

Wind Engineering Institute of Korea, Vol. 19,

No. 1, pp. 9

∼

14 (in Korean).

Analysis of Archimedes Spiral Wind Turbine Performance by Simulation and Field Test

Article

Full-text available

Dec 2019

In this study, the performance of an Archimedes spiral wind turbine is analyzed by simulation and validated by a field test. It is characterized as a horizontal-axis drag-type wind turbine. This type of wind turbine cannot be analyzed by the well-known Blade Element Momentum(BEM) theory or Double Stream Tube Method(DSTM) commonly used to analyze the performance of lift-type wind turbines. Therefore, the computational fluid dynamics (CFD) method was applied. From the simulation, the power coefficient, known as the mechanical efficiency of the rotor, the tip speed ratio was obtained. The maximum power coefficient, and the corresponding tip speed ratio were found to be 0.293 and 2.19, respectively. In addition, the electrical efficiency with respect to the rotational speed of the generator was obtained through generator–controller test. The obtained mechanical and electrical efficiencies were used to predict the power curve of the wind turbine. Finally, the predicted performance of the wind turbine, including the electrical losses, was validated by the field test. The maximum error between the prediction and the measured power was found to be less than 7.80%.

Performance Prediction and Validation of a Small-Capacity Twisted Savonius Wind Turbine

Article

Full-text available

May 2019

In this study, an off-grid–type small wind turbine for street lighting was designed and analyzed. Its performance was predicted using a computational fluid dynamics model. The proposed wind turbine has two blades with a radius of 0.29 m and a height of 1.30 m. Ansys Fluent, a commercial computational fluid dynamics solver, was used to predict the performance, and the k-omega SST model was used as the turbulence model. The simulation result revealed a tip-speed ratio of 0.54 with a maximum power coefficient, or an aerodynamic rotor efficiency of 0.17. A wind turbine was installed at a measurement site to validate the simulation, and a performance test was used to measure the power production. To compare the simulation results obtained from the CFD simulation with the measured electrical power performance, the efficiencies of the generator and the controller were measured using a motor-generator testbed. Also, the control strategy of the controller was found from the field test and applied to the simulation results. Comparing the results of the numerical simulation with the experiment, the maximum power-production error at the same wind speed was found to be 4.32%.

Analysis of Environmental Conditions for the Conceptual Design of a 200 MW Floating Offshore Wind Farm in the East Sea, Korea

Conference Paper

Dec 2019

Due to global climate change, concern regarding the environment is greater than ever. Also, the energy industry is constantly developing and investing in new and renewable energy to reduce carbon emissions. Korea is planning to increase the proportion of renewable energy generation to 20% by 2030, in accordance with the 3020 renewable energy policy. This will involve 16.5 GW (34%) from wind energy, with a capacity from offshore wind energy of approximately 13 GW. Considering domestic technological wind resource potential (33.2 GW), it seems to be a sufficient target amount. However, in order to start the wind power generation business, the installation area must be analyzed for environmental information, for the evaluation of the wind resource and the early-stage concept design. Because it is difficult to conduct long-term measurements of the entire sea area, the environmental conditions are generally estimated from short-term measurement data and long-term reanalysis data. In this study, the environmental conditions of the East Sea of Korea were selected, and a comparative analysis was performed on the meteorological agency’s oceanic meteorology buoy data, ERA-5 reanalysis data obtained from ECMWF, and NASA’s MERRA-2 data. The extreme sea states of 50 years and 100 years were analyzed by extreme statistical analysis. Finally, environmental conditions required for the basic design of wind turbines were selected following IEC and DNV standards.

Analysis of Numerical Modeling Techniques for Offshore Wind Resource Map

Article

Full-text available

Jul 2024

Offshore wind resource maps are the primary data for wind power project, national renewable energy supply policy, and power grid planning. In this study, we discussed trends in wind resource map production technology. A survey has been performed focusing on production technology and application status of wind resource maps for the representative countries such as the European Union (Denmark), the United States, and Japan. To improve national offshore wind resource maps, they have basically been enhanced to better quality wind resources and their uncertainties using ensemble mesoscale numerical modeling or coupled meso-microscale numerical modeling. The application of the model design for physical schemes varied in regions. As a result, it is necessary to adopt advanced numerical model and perform optimal experimental design to develop a new offshore wind resource map of South Korea. Particularly, we identified that vertically extended wind resource maps within the planetary boundary layer (around 300 m above sea level) are common features. This system accurately provides long-term wind characteristics for identifying suitable wind farm locations, considering the increase in the turbine sizes.

Regression Analysis on Global Wind Speed Using Reanalysis Data

Article

Full-text available

Dec 2021

Although the reanalysis data has low spatial resolution, it can be used for long-term correction of wind resources and high-resolution downscaling in conjunction with numerical weather prediction or computational fluid dynamics. In this study, regression analysis of the global wind speed as a function of topographic factors was carried out, and the possibility of its use in high resolution downscaling was tested. According to the regression results by various morphometric features, the fitness of multiple linear regression, machine learning models, i.e., neural network and random forest models, showed R2 of 0.71, 0.95, and 1.00, respectively. Among the topographic factors, latitude, cell area, terrain elevation, longitude, and terrain openness were found to have the highest explanatory capability in the order. Compared to the conventional neural network, the modified twin neural network model has a performance improvement effect regarding imbalanced dataset. Nevertheless the neural network structure used in this research was not precise to reproduce non-linearity of the given data, however, which was possible with introduction of the random forest model.

Estimation of Reference Wind Speeds in Offshore of the Korean Peninsula Using Reanalysis Data Sets

Article

Full-text available

Dec 2021

To determine the wind turbine class in the offshore of the Korean Peninsula, the reference wind speed for a 50-y return period at the hub height of a wind turbine was estimated using the reanalysis data sets. The most recent reanalysis data, ERA5, showed the highest correlation coefficient (R) of 0.82 with the wind speed measured by the Southwest offshore meteorological tower. However, most of the reanaysis data sets except CFSR underestimated the annual maximum wind speed. The gust factor of converting the 1 h-average into the 10 min-average wind speed was 1.03, which is the same as the WMO reference, using several meteorological towers and lidar measurements. Because the period, frequency, and path of typhoons invading the Korean Peninsula has been changing owing to the climate effect, significant differences occurred in the estimation of the extreme wind speed. Depending on the past data period and length, the extreme wind speed differed by more than 30% and the extreme wind speed decreased as the data period became longer. Finally, a reference wind speed map around the Korean Peninsula was drawn using the data of the last 10 years at the general hub-height of 100 m above the sea level.

Performance Test of 3D Printed Blades for a Scaled Wind Turbine in a Wind Tunnel

Article

Sep 2020

In this study, blades manufactured by 3D printing technology were experimentally tested to be used for a scaled wind turbine in a wind tunnel. The scaled model was originally designed and manufactured by researchers at the Technical University of Munich. The model has been slightly modified to adopt the 3D printed blades for this study. Also, control algorithms for the power maximization in the low wind speed regions were constructed and applied to a commercial programmable logic controller for wind tunnel tests of the scaled model. For comparison, the scaled model was also modeled in MATLAB/Simulink and dynamic simulations were performed with the measured wind speed as an input. The simulation results seemed to overpredict the experimental results initially, but by considering the unexpected extra generator torque due to friction of the shaft, the errors were reduced to be less than 5%. Based on this study, the application of 3D printed blades to the wind turbine scaled models of a similar rotor diameter was found to be an efficient and effective way of blade manufacturing and scaled model testing. © 2020 Korean Society for Precision Engineeing. All rights reserved.

Review of Onshore Wind Resource Map Development and Public Service

Article

Full-text available

Jul 2020

Onshore wind resource maps are the primary data for wind farm site prospecting, national renewable energy supply policy and power system network design development. This study discusses appropriate service levels in terms of elements and spatiotemporal resolution in wind resource maps, with a view to improving the wind resource map service in Korea. The study investigated the production technology and service status of the wind resource maps currently in use in Europe, the United States, Australia, and Japan. As a result, it identified that a capacity factor map should be included in order to perform more direct measurements close to wind power generation, and that various wind resource maps, along with wind speeds, need to be included, such as surface geographical maps and environmental conservation maps. In particular, the spatial resolution of wind resource maps should be improved to within 200 m, with the inclusion of horizontal grid pacings, and up to 200 m above ground level vertically in the same manner as in Europe and the United States. It is expected that the improved service proposed by this paper will be more useful to policy makers, the wind power industry, and wind energy researchers.

Evaluation of Surface Observation Data for Wind Resource Assessment of Ulleungdo

Article

Full-text available

Mar 2019

Since Ulleungdo, which is a steep complex terrain island, has very strong local wind characteristics, the validity of surface observation data should be evaluated first when applying surface observation data to wind resource assessment. In this paper, the local meteorological representations of surface observation data were evaluated by analyzing the correlation between the reanalysis data or the mesoscale numerical weather prediction results as synoptic meteorological input data versus the surface observation data in Ulleungdo. We also estimated how consistent the predicted results of the synoptic meteorological data are with the surface observation data when computational flow analysis is performed to account precisely for flow deformation caused by the topography. The prediction error of micrositing is confirmed to increase as the terrain becomes complex, which is expressed as terrain complexity indices. The surface observation data of Ulleungdo showed strong local wind characteristics, except the data of Hyunpori where a high-rise meteorological tower was erected. Since computational fluid dynamics would not simulate the wind system effect even if the terrain complexity is accurately considered, the uncertainty of wind resource assessment relying on surface observation data is deemed considerably large. Therefore, installing a high-rise meteorological tower in the candidate wind farm site is inevitable in accordance with the IEC 61400-12 guideline.

Analysis and Validation of a Small Capacity Wind Turbine with a Side Furling System

Article

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Comparative Evaluation of the Third-Generation Reanalysis Data for Wind Resource Assessment of the Southwestern Offshore in South Korea

Article

Full-text available

Feb 2018

This study evaluated the applicability of long-term datasets among third-generation reanalysis data CFSR, ERA-Interim, MERRA, and MERRA-2 to determine which dataset is more suitable when performing wind resource assessment for the ‘Southwest 2.5 GW Offshore Wind Power Project’, which is currently underway strategically in South Korea. The evaluation was performed by comparing the reanalyses with offshore, onshore, and island meteorological tower measurements obtained in and around the southwest offshore. In the pre-processing of the measurement data, the shading sectors due to a meteorological tower were excluded from all observation data, and the measurement heights at the offshore meteorological towers were corrected considering the sea level change caused by tidal difference. To reflect the orographic forcing by terrain features, the reanalysis data were transformed by using WindSim, a flow model based on computational fluid dynamics and statistical-dynamic downscaling. The comparison of the reanalyses with the measurement data showed the fitness in the following order in terms of coefficient of determination: MERRA-2 > CFSR = MERRA > ERA-Interim. Since the measurement data at the onshore meteorological towers strongly revealed a local wind system such as sea-land breeze, it is judged to be inappropriate for use as supplementary data for offshore wind resource assessment.

Long-Term Wind Resource Assessment of Shinan-gun Bigeum-do Using The Wind Farm SCADA Data and Reanalysis Data

Article

Full-text available

Jan 2013

Long-term wind resource assessment has been carried out for Shinan-gun Bigeum-do where an offshore wind project is planning in succession of the onshore wind farm development. SCADA data of the Shinan Wind Power Plant and LIDAR measurements were selected as trustful wind resource datasets representing the local climatology by correlation analysis. Long-term correction has been carried out by the matrix time-series MCP taking MERRA reanalysis data as a reference dataset. The 34-year wind index was calculated from the long-term correction data sop that the variability of wind speed and wind power generation were evaluated as 2.0% and 5.4%, respectively, and its uncertainty were 1.2% and 2.8%, respectively. It is noticeable that wind index increased since 2010 comparing with long-term average for 34 years possibly due to an enforcement of La Niña effect.

Comparative Analysis on Commercial Wind Resource Maps of South Korea

Article

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Jan 2015

Demand for a wind resource map, which is core information for wind resource assessment, is increasing in accordance with the sharp expansion of wind energy dissemination worldwide. The global wind resource map as a commercial service also gives the official status fast. Nonetheless, there is a need to evaluate the reliability of those high-priced commercial services. This paper presents a comparative analysis of two kinds of commercial wind resource maps of South Korea provided by overseas service companies and Korea Institute of Energy Research. The systematic conformity of the wind resource map is analyzed, such as meteor-statistical correlation of wind power density and terrain elevation, comparison of the Weibull shape factor as a measure of wind speed distribution, wind profile exponent describing the vertical wind profile characteristics, etc.

Wind Resource Assessment on the Western Offshore of Korea Using MERRA Reanalysis Data

Article

Full-text available

Jan 2013

Massive offshore wind projects of have recently been driven in full gear on the Western Offshore of Korea including the 2.5 GW West-Southern Offshore Wind Project of the Ministry of Trade, Industry and Energy, and the 5 GW Offshore Wind Project of the Jeollanamdo Provincial Government. On this timely occasion, this study performed a general wind resource assessment on the Western Offshore by using the MERRA reanalysis data of temporal-spatial resolution and accuracy greatly improved comparing to conventional reanalysis data. It is hard to consider that wind resources on the Western Sea are excellent, since analysis results indicated the average wind speed of 6.29 ± 0.39 m/s at 50 m above sea level, and average wind power density of 307 ± 53 W/m 2. Therefore, it is considered that activities shall be performed for guarantee economic profits from factor other than wind resources when developing an offshore wind project on the Western Offshore.

The NCEP climate forecast system reanalysis

Article

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Aug 2010

The reanalysis at National Centers for Environmental Prediction (NCEP) focuses on atmospheric states reports generated by a constant model and a constant data assimilation system. The datasets have been exchanged among national and international partners and used in several more reanalyses. The new data assimilation techniques have been introduced including three-dimensional variational data assimilation (3DVAR), 4DVAR, and ensembles of analyses such as ensemble Kalman filter (EnKF), which produce not only an ensemble mean analysis but also a measure of the uncertainty. The new climate forecast system reanalysis (CFSR) was executed to create initial states for the atmosphere, ocean, land, and sea ice that are consistent as possible with the next version of the climate forecast system (CFS) version 2, which is to be implemented operationally at NCEP in 2010. Several graphical plots were generated automatically at the end of each reanalyzed month and were displayed on the CFSR Web site in real time.

Ncep-Doe amip-Ii reanalysis (R-2)

Article

Full-text available

Nov 2002

The NCEP-DOE Atmospheric Model Intercomparison Project (AMIP-II) reanalysis is a follow-on project to the "50-year" (1948-present) NCEP-NCAR Reanalysis Project. NCEP-DOE AMIP-II reanalysis covers the "20-year" satellite period of 1979 to the present and uses an updated forecast model, updated data assimilation system, improved diagnostic outputs, and fixes for the known processing problems of the NCEP-NCAR reanalysis. Only minor differences are found in the primary analysis variables such as free atmospheric geopotential height and winds in the Northern Hemisphere extratropics, while significant improvements upon NCEP-NCAR reanalysis are made in land surface parameters and land-ocean fluxes. This analysis can be used as a supplement to the NCEP-NCAR reanalysis especially where the original analysis has problems. The differences between the two analyses also provide a measure of uncertainty in current analyses.

The ERA-Interim reanalysis: Configuration and performance of the data assimilation system

Article

Full-text available

Apr 2011

ERA-Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim project was conducted in part to prepare for a new atmospheric reanalysis to replace ERA-40, which will extend back to the early part of the twentieth century. This article describes the forecast model, data assimilation method, and input datasets used to produce ERA-Interim, and discusses the performance of the system. Special emphasis is placed on various difficulties encountered in the production of ERA-40, including the representation of the hydrological cycle, the quality of the stratospheric circulation, and the consistency in time of the reanalysed fields. We provide evidence for substantial improvements in each of these aspects. We also identify areas where further work is needed and describe opportunities and objectives for future reanalysis projects at ECMWF.

The NMC/NCAR 40-year reanalysis project. Bull Am Meteorol Soc

Article

Full-text available

Mar 1996

The NCEP and NCAR are cooperating in a project (denoted "reanalysis") to produce a 40-year record of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involves the recovery of land surface, ship, rawinsonde, pibal, aircraft, satellite, and other data; quality controlling and assimilating these data with a data assimilation system that is kept unchanged over the reanalysis period 1957-96. This eliminates perceived climate jumps associated with changes in the data assimilation system. The NCEP/NCAR 40-yr reanalysis uses a frozen state-of-the-art global data assimilation system and a database as complete as possible. The data assimilation and the model used are identical to the global system implemented opera- tionally at the NCEP on 11 January 1995, except that the horizontal resolution is T62 (about 210 km). The database has been enhanced with many sources of observations not available in real time for operations, provided by different coun- tries and organizations. The system has been designed with advanced quality control and monitoring components, and can produce 1 mon of reanalysis per day on a Cray YMPI8 supercomputer. Different types of output archives are being created to satisfy different user needs, including a "quick look" CD-ROM (one per year) with six tropospheric and stratospheric fields available twice daily, as well as surface, top-of-the-atmosphere, and isentropic fields. Reanalysis information and selected output is also available on-line via the Internet (http//:nic.fb4.noaa.gov:8000). A special CD- ROM, containing 13 years of selected observed, daily, monthly, and climatological data from the NCEP/NCAR Re- analysis, is included with this issue. Output variables are classified into four classes, depending on the degree to which they are influenced by the observations andlor the model. For example, "C" variables (such as precipitation and surface fluxes) are completely determined by the model during the data assimilation and should be used with caution. Never- theless, a comparison of these variables with observations and with several climatologies shows that they generally contain considerable useful information. Eight-day forecasts, produced every 5 days, should be useful for predictabil- ity studies and for monitoring the quality of the observing systems. The 40 years of reanalysis (1957-96) should be completed in early 1997. A continuation into the future through an identical Climate Data Assimilation System will allow researchers to reliably compare recent anomalies with those in earlier decades. Since changes in the observing systems will inevitably produce perceived changes in the climate, par- allel reanalyses (at least 1 year long) will be generated for the periods immediately after the introduction of new ob- serving systems, such as new types of satellite data. NCEP plans currently call for an updated reanalysis using a state-of-the-art system every five years or so. The suc- cessive reanalyses will be greatly facilitated by the generation of the comprehensive database in the present reanalysis.

The NCEP/NCAR reanalysis 40-year project

Article

Jan 1996
B AM METEOROL SOC

MERRA: NASA's Modern-Era Retrospective analysis for Research and Applications

Article

Jul 2011

The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA’s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA’s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. Focusing on the satellite era, from 1979 to the present, MERRA has achieved its goals with significant improvements in precipitation and water vapor climatology. Here, a brief overview of the system and some aspects of its performance, including quality assessment diagnostics from innovation and residual statistics, is given. By comparing MERRA with other updated reanalyses [the interim version of the next ECMWF Re-Analysis (ERA-Interim) and the Climate Forecast System Reanalysis (CFSR)], advances made in this new generation of reanalyses, as well as remaining deficiencies, are identified. Although there is little difference between the new reanalyses in many aspects of climate variability, substantial differences remain in poorly constrained quantities such as precipitation and surface fluxes. These differences, due to variations both in the models and in the analysis techniques, are an important measure of the uncertainty in reanalysis products. It is also found that all reanalyses are still quite sensitive to observing system changes. Dealing with this sensitivity remains the most pressing challenge for the next generation of reanalyses. Production has now caught up to the current period and MERRA is being continued as a near-real-time climate analysis. The output is available online through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC).