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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.
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9
한국풍공학회논문집, 19, 1, (2015) 9~14
(투고일:2015.1.26/심사완료일:2015.3.18/게재확정일:2015.3.23)
상업용 남한 풍력자원지도의 비교분석
Comparative Analysis on Commercial Wind Resource Maps of South Korea
김현구1)·강용혁2)·윤창열3)
Kim, Hyun-Goo·Kang, Yong-Heack·Yun, Chang-Yeol
···························· ···················· ···················· ····················· ················· ···················· · ···················· ···················· ····
Abstract :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.
Key words : Wind Resource Map, Numerical Weather Prediction, South Korea, Wind Power Density, Weibull Shape Parameter, Wind
Profile Exponent
요약 : 풍력보급의 급성장에 따라 풍력자원평가의 핵심자료인 풍력자원지도의 수요도 증가하고 있다. 이에 따라 전세계를 대상으로
상업용 풍력자원지도 서비스가 본격화되고 있다 . 고가의 상업용 풍력자원지도를 선택하기에 앞서 신뢰도를 확인할 필요가 있다.
연구에서는 남한을 대상으로 해외 상업용 풍력자원지도 2종과 한국에너지기술연구원의 풍력자원지도를 비교분석하였다 . 특히
상통계학적으로 해발고도에 따른 풍속 풍력밀도의 상관성, 시계열 풍속분포의 척도인 와이블 형상계수, 연직 풍속분포의 척도인
속분포지수 등에 대해 체계적인 일치성을 비교분석함으로써 상업용 풍력자원지도의 신뢰도를 평가할 있는 방법을 제시하였다.
키워드
:
풍력자원지도
,
수치기상예측
,
남한
,
풍력밀도
,
와이블
형상계수
,
풍속분포지수
···························· ···················· ···················· ····················· ················· ···················· · ···················· ···················· ····
1. 서론
최근
들어
국가적
차원에서
체계적이며
전략적인
풍력자원
개발을
위하여
국가
규모의
풍력자원지도를
구축하여
활용
하는
추세이다
.
미국
에너지부
(US DOE; Dept. of Energy)
2010
년에
재생
에너지연구소
(NREL; National Renewable Energy Laboratory)
통해
미국
풍력자원지도의
수평면
공간해상도를
2.5km
향상시키고
·
해상
풍력자원
잠재량을
재계산
하였다
.
(1)
아프리카공화국
에너지부는
2014
년에
UNDP-GEF
덴마크의
기술공여를
통해
남아공
풍력자원지도를
마련하였으며
,
(2)
우디아라비아의
KACARE(King Abdullah City Atomic and
Renewable Energy)
미국
재생에너지연구소의
기술을
도입하
사우디아라비아
풍력자원지도를
개발
중에
있다
.
(3)
우리나라는
산업통상자원부
산하
한국에너지기술연구원
(KIER; Korea Institute of Energy Research)
통해
2007
저해
상도
(9km
)
남한
풍력자원지도를
개발하여
공개한
이후
2008
중해상도
(3km
), 2009
고해상도
(1km
)
지속적으로
·
공간해상도
정확도를
향상시켜오고
있다
.
(4)
한국에너지기술연구원에서
제작한
풍력자원지도는
전국
150
지점에서
IEC
국제풍력표준에
의거하여
수행된
기상탑
(meteorological tower)
측정자료를
(5)
이용하여
육상풍에
대해
정확도를
검증하였다
.
또한
풍속연직구조에
대해서는
LiDAR,
SODAR
이용하여
지상기반
원격탐사
캠페인을
수행하고
(6-8)
이를
이용하여
검증하였다
.
해상에서는
해상부이
(marine buoy;
기상청
5, KIER 1)
이용한
검증
ENVISAT, RADARSAT-1
인공위성에서
촬영된
SAR(Synthetic Aperture Radar)
위성영상
으로부터
해상풍을
추출하여
풍력자원지도를
검증하였다
.
(9-11)
국가
차원에서
풍력자원지도를
구축하는
이유는
정책적
요성과
산업적
활용도가
매우
높기
때문이다
.
,
정책적으로는
풍력자원
잠재량을
정확히
산정하여
실현가능한
보급목표를
설정하기
위함이며
,
산업적으로는
풍력자원개발의
핵심자료를
공공자료로
제공함으로써
풍력개발을
촉진시키기
위함이다
.
우리나라는
산업통상자원부에서
한국에너지기술연구원의
재생에너지
자원지도
(kredc.kier.re.kr)
기반으로
신재생에너
지기본계획을
수립해오고
있다
.
신재생에너지
자원지도는
재생에너지분야
이외에도
지자체의
풍수해저감종합계획
·
산업
·
연구분야에서
핵심적인
기초자료로서
다양하게
활용
1)
정회원
,
교신저자
,
한국에너지기술연구원
,
신재생에너지자원센터
,
공학박사
(hyungoo@kier.re.kr)
2)
한국에너지기술연구원
,
신재생에너지자원센터장
(yhkang@kier.re.kr)
3)
한국에너지기술연구원
,
신재생에너지자원센터
(yuncy@kier.re.kr)
10 김현구·강용혁 ·윤창열
Journal of the Wind Engineering Institute of Korea
되고
있다
.
그런데
국가
차원에서
풍력자원지도를
개발할
있는
경제
,
기술적
능력이
있거나
국제적
개발원조
또는
선진국의
기술
지원을
받아서
국가
풍력자원지도를
개발한
국가는
소수에
과하다
.
따라서
국가
풍력자원지도를
보유하지
못한
대부분
가의
잠재적
수요를
겨냥한
상업용
풍력자원지도
서비스가
성화되고
있는
추세이다
.
(12)
논문에서는
육해상에서
다각도의
검증을
통하여
불확도
파악한
한국에너지기술연구원의
남한
풍력자원지도를
기준
으로
하여
대표적인
해외
풍력자원평가
서비스사의
상업용
력자원지도를
비교분석하였다
.
이때
통계적
,
공간적
비교분석
수행함으로써
상업용
풍력자원지도의
신뢰도
이를
선택
감수해야할
불확도
수준을
확인하였다
.
2. 자료 방법
논문에서는
한국에너지기술연구원에서
작성하고
검보정
중해상도
(
공간해상도
3km
)
남한
풍력자원지도와
스위
SANDER+PARTNER(www.sander-partner.ch)
그리고
미국
3TIER(www.3tier.com)
에서
작성하여
판매하는
남한
풍력자원
지도를
입수하여
비교분석하였다
.
참고로
한국에너지기술연구
원의
남한
풍력자원지도는
학술연구
또는
공공성
사업일
경우
무상으로
제공된다
.
국가
풍력자원지도는
광범위한
영토
·
영해
전체면적에
작성되어야
하므로
,
중규모
(mesoscale)
수치기상예측
(NWP;
numerical weather prediction)
모델에
재해석자료
(reanalysis
data)
자료동화
(data assimilation)
하는
방법이
사용된다
.
Tab l e 1
한국에너지기술연구원
(KIER), SANDER+PARTNER
(S&P)
그리고
3TIER
에서
제공하는
남한
풍력자원지도의
기술
사양을
비교하였다
.
풍력발전량은
풍속의
세제곱에
비례하기
때문에
풍력자원의
실질적
평가지표는
평균풍속이
아니라
풍력밀도
(wind power
density, W/m
2
)
이며
,
평균
풍력밀도는
다음
식으로
계산된다
.
(1)
식에서
아래첨자
i
i
-
번째
평균시간이며
N
평균시간
으로
, 1
시간
-
평균
1
년간의
시계열자료일
경우
N
=24
×
365 =
8,760
이다
.
그리고
A
풍력터빈
블레이드의
회전면적
(m
2
),
ρ
공기밀도
(kg/m
3
)
이다
.
3TIER
S&P
WRF(Weather Research Forecasting)
모델
NCAR/NCEP
재해석자료를
자료동화하여
5km
공간해상도
수치모의하였다
.
그러나
제작시점이
이들보다
빠른
KIER
MM5
모델을
사용하여
3km
공간해상도로
수치모의하였고
,
해석자료로는
한국
기상청
RDAPS(Regional Data Assimilation
and Prediction System)
해상에서는
QuikSCAT
위성자료를
가로
자료동화하였다
.
앞서
언급한
바와
같이
남한에
특화된
해석자료를
사용하였으며
다각도의
검보정을
수행한
KIER
력자원지도의
정확도가
상업용
풍력자원지도보다
우수할
것으
예상된다
.
3TIER
자체적으로
동아시아에
대해
자사의
풍력자원지
도를
검증한
바에
의하면
연평균풍속의
바이어스
(bias) +0.86
m/s, RMSE
오차
1.22m/s
보고하고
있다
.
(13)
그런데
3TIER
자체검증에
사용한
US NCEP ADP(National Centers for
Environmental Prediction Automated Data Processing)
지상관측
자료의
경우
.
관측고도가
지상
10m
이다
.
한편
우리나라에서
형고도에
따른
풍속할증
상관성을
분석한
바에
의하면
(14)
특히
산악지역의
지상관측자료가
지형고도가
높아질수록
풍속할증
증가하는
풍공학적
특성을
제대로
반영하지
못하기
때문에
지상관측자료를
이용한
풍력자원지도의
검증은
실효성이
없다
판단된다
.
S&P
측정고도
40m
이상인
기상탑
(meteorological mast)
정자료를
이용하여
자체검증하였으나
폴란드의
해안지역
자료
만을
사용하였기
때문에
이를
남한까지
확대적용하기에는
리가
따른다
.
(15)
KIER
S&P
각각
1
시간
-
간격
3
년간
(2005~2007
)
10
-
간격
1
년간
(2010
)
대한
격자점에서의
높이에
대한
시계열자료를
제공하지만
3TIER
비싼
가격에도
불구하고
50m
높이
층에
대해
육상의
평균
풍력밀도
요소만을
공한다
.
만일
평균풍속
등의
요소와
추출고도를
추가할
경우
비례하여
가격이
상승한다
. Table 1
제시된
가격이
학술연
구용
할인율
50%
적용된
점을
고려한다면
상업용일
경우
당한
고가로
가격부담이
매우
자료이다
.
한국에너지기술연구원의
풍력자원지도와
해외
상업용
풍력
자원지도를
비교함에
있어서
공간분포의
비교분석
이외에도
지형고도와
기상요소
(
풍속
,
풍력밀도
,
와이블
형상계수
그리고
풍속분포지수
)
간의
통계적
상관성을
분석함으로써
수치기상
예측
상의
체계적
오차에
대해서도
하였다
.
직하게는
실제
측정자료와
풍력자원지도
예측자료를
비교하되
시계열자
료에
대하여
통계분석함으로써
정확도를
하여야
으나
,
시계열자료의
비교시점
해상도에
따른
측정위치
부정합성
,
추가의
구입비용
등의
으로
인하여
연구에서는
시계열
자료
대신
공간분포자료에
대하여
비교분석하였다
.
동일한
고도에서
풍력자원지도의
기상요소를
비교하기
KIER
3TIER
지상고도
50m
레이어
(layer)
대해
, KIER
S&P
지상고도
60m
레이어에
대해
비교분석하였다
.
이를
P
A
--- 1
N
----1
2
---ρiVi
3
⎝⎠
⎛⎞
i1=
N
=
Table 1 Specifications of South Korea wind resource maps
KIER 3TIER S&P
NWP model MM5 WRF WRF
Reanalysis data RDAPS/QSCAT NCAR/NCEP NCAR/NCEP
Spatial resolution 3km 5km 5km
Temporal coverage 2005~2007 10-year 2010
Extraction heights 20, 70, 140m 50m 60, 120, 150m
Meteorological
variables*V, D, P, T P V, D, P, T
Time-series interval 1hr - 10min
Academic price Free of charge 10,000 USD 9,000 EURO
*Wind speed (V), wind direction (D), wind power density (P), air temperature
(T).
상업용 남한 풍력자원지도의 비교분석 11
한국풍공학회논문집,19권제1, 2015
위하여
20m, 70m, 140m
높이의
KIER
격자점
시계열자료를
지상고도
50m
60m
내삽
(interpolation)
하였다
.
.
풍속분포
지수식
(power-law equation)
으로부터
유도된
(2)
로부터
풍속분포지수
(wind profile exponent,
α
)
계산
하였다
.
(2)
격자점에서
풍속분포지수를
산출하면
(3)
(4)
로부터
50m
60m
높이에서의
풍속과
풍력밀도를
계산할
있다
.
(3)
(4)
연구에서
사용한
풍력자원지도는
공간해상도
,
추출고
,
해석기간
시간간격
등이
상이하기
때문에
특정지점
에서의
기상요소에
대한
비교보다는
수치기상예측
모의
과의
체계적
특성에
대한
통계분석을
통해
유의한
차이점을
하고자
하였다
.
3. 결과 고찰
3.1
공간분포
비교분석
Fig. 1
지면고도
50m
에서
KIER
3TIER
평균
풍력밀도
공간분포를
비교한
것이다
.
참고로
3TIER
풍력자원지도에는
해상이
포함되지
않았
때문에
육상에
대해서만
비교가
가능
하다
.
참고로
공간해상도
5km
자료는
크리
(Kriging)
내삽
통해
공간해상도
3km
변환함으로써
동일
격자점에
대해
교하였다
.
공간해상도가
3TIER
5km
비해
3km
높은
KIER
력밀도
분포도는
지형특성을
보다
정확하게
하고
있으며
,
자료간의
차이는
공간해상도에
따라
상대적으로
지형고도
차이가
적은
평지에서는
풍력밀도의
차이가
거의
없지만
대인
산악지형에서는
풍력밀도
예측의
과소
·
과대
경향이
뚜렷
하게
타난
.
,
저해상도에서는
백두대간
능선의
중심
위치가
격자해상도에
의해
이격
(shift)
따라
능선을
심으로
풍상부와
풍하부가
각각
과소
·
과대
예측되는
경향이
타난
.
우리나라는
대부분의
풍력단지가
내륙
고산지대에서
개발되므로
고해상도의
풍력자원지도가
요구되며
,
공간해상도
3TIER
활용성은
매우
다고
판단된다
.
Fig. 2
지면고도
60m
에서
KIER
S&P
평균
풍속
공간
분포를
비교한
것으로
,
전반적으로
S&P
풍속을
과대예측하
α
ln V1
()ln V2
()
ln z1
() z2
()ln
-----------------------------------
=
V
V1
----- z
z1
----
⎝⎠
⎛⎞
α
=
P
P1
----- z
z1
----
⎝⎠
⎛⎞
3α
=
Fig. 1 Mean wind power density maps (50m above ground level)
Fig. 2 Mean wind speed maps (60m above ground level)
12 김현구·강용혁 ·윤창열
Journal of the Wind Engineering Institute of Korea
있다
.
자료간의
풍속차이
분포를
보면
해상
산악지역
에서
S&P
과대예측이
뚜렷하게
나며
내륙
평지에서는
차이가
어드는
경향을
보인다
.
3.2
기상통계
비교분석
공간해상도가
상이한
자료의
공간분포
비교분석을
위해
동일
래스터
(raster)
변환
경우
,
내삽
공간해상도의
화에
따라
자료의
왜곡
발생한다
.
따라서
공간분포
분석은
정성적인
비교를
위함이며
,
직하게는
기상통계
분석을
통하여
각각의
자료가
기상학적
특성의
유효성을
비교하여야
것이다
.
제작기관
풍력자원지도의
신뢰성을
평가하기
위하여
기상
통계학적
비교분석을
수행하였다
.
육상
풍력자원의
경우
해발
고도에
따라
풍속
풍력밀도가
증가하는
경향이
뚜렷하게
나야
한다
.
(16)
따라서
이러한
기상통계학적
특성이
수치기상
예측
과에
반영되는지를
분석함으로써
풍력자원지도의
효성을
확인할
있다
.
Fig. 3
KIER
3TIER
평균
풍력밀도를
비교한
것이다
.
(a)
육상에서
해발고도
도를
보면
KIER(
파란
)
3TIER
(
)
해발고도가
상승할수록
풍력밀도가
증가하는
향을
보인다
.
그래프에서
실선과
점선은
각각
KIER
3TIER
산점도의
이동평균이다
. (b)
풍력밀도
산포도를
보면
,
자료
간의
합도는
1.07,
정계수
(R
2
) 0.57
정성적으로
유사함을
확인할
있다
.
Fig. 4
KIER
S&P
평균풍속을
비교한
것이다
. (a)
육상
에서
풍속의
해발고도
도를
보면
KIER(
파란
)
S&P(
)
해발고도가
상승할수록
풍력밀도가
증가하지만
S&P
+1.35m/s
바이어스를
가지는
것으로
타났
. (b)
(
)
해상
(
파란
)
에서
풍속
산포도를
보면
,
자료간
정계수
(R
2
)
육상과
해상이
각각
0.82, 0.87
합도가
높지만
기는
각각
0.65, 0.77
KIER
대비
S&P
30%
과대예측하고
있다
.
풍력발전량을
계산하기
위해서는
풍력터빈
허브
(wind turbine
hub)
높이에서의
통계적
풍속분포를
아야
한다
.
일반적으로
기간
풍속분포는
와이블
분포를
때문에
다음의
와이블
분포함수
(Weibull probability distribution function)
표현할
있다
.
(5)
f
V() k
c
-- V
c
---
⎝⎠
⎛⎞
k1
exp V
c
---
⎝⎠
⎛⎞
k
=
Fig. 3 Comparison of wind power density for KIER (blue) and 3TIER (red)
Fig. 4 Comparison of wind speed for KIER and S&P
상업용 남한 풍력자원지도의 비교분석 13
한국풍공학회논문집,19권제1, 2015
식에서
c
k
각각
와이블
등급계수
(scale factor)
형상계
(shape factor)
이다
.
Fig. 5
KIER(
파란
)
S&P(
)
해발고도에
따른
이블
형상계수를
비교분석한
것이다
.
우리나라에서
풍력자원
우수한
도에서
기상탑
측정자료
30
지점
기상청
지면
기상관측자료
19
지점으로부터
산출한
통계분석에
의하면
와이
형상계수는
최소
1.34,
최대
2.2
범위에서
평균
1.74±0.21
가진다
.
(5)
이를
참조할
KIER
형상계수
분포는
의한
범위에
있으나
S&P
+0.5
바이어스를
보이고
있어
의한
범위를
초과하였기
때문에
자료의
신뢰성이
어진다
.
Fig. 6
KIER
S&P
풍속분포지수를
비교한
산포도로
(
파란
)
육상
(
)
구분하여
도시하였다
.
특이하게
속분포지수
산포도는
비선형적인
상관관계를
보이고
있다
.
,
지표면
기가
없어서
풍속분포지수가
해상에서는
그함수의
추세를
보이며
지표면
기가
높은
육상은
지수함
수의
추세를
보이되
해상과
육상의
이지역으로
판단되는
α
=
1/7
부근에서
상이한
함수형
추세가
되고
있다
.
해상에서는
KIER
비해
S&P
풍속분포지수가
과소경향
보이며
이는
Fig. 2(c)
에서
S&P
해상
풍속
과대예측과
적인
관련이
있다
.
반대로
육상에서는
S&P
풍속분포지수
과대한
경향을
보이고
있어
S&P
수치기상예측에
체계적
문제가
있음을
시사한다
.
4. 결론
해외
풍력자원평가
서비스사로부터
구입할
있는
상업용
풍력자원지도의
신뢰도를
점검하기
위하여
다각도의
검증을
정확도가
확인된
한국에너지기술연구원의
남한
풍력자원
지도를
기준으로
하여
공간분포
기상통계에
대한
비교분석
수행하였다
.
연구에서
도출한
결론
다음과
같다
.
(1)
전세계를
대상으로
풍력자원지도는
중규모
수치기상
예측
모델에
전지구
재해석자료를
자료동화하여
서비스하고
있으며
공간해상도
5km
이하로
제작하고
있다
.
그러나
전지구
대한
동일
수준의
검증이
때문에
일부
검증을
통하
보정한
지역을
제외하면
해석과는
상당한
불확도를
것으로
우려된다
.
반면
한국에너지기술연구원에서
구축한
남한
풍력자원지도의
경우
한반도에
최적화된
리모형
력자료
그리고
신뢰도
높은
측정자료를
이용하여
검보정하였
때문에
해외
풍력자원지도와
비교하여
신뢰도가
상대적으
높다고
판단된다
.
(2)
미국
3TIER
KIER
비해
공간해상도로
인하여
지형고도의
이격이
타났
.
그러나
기상통계학적으로는
발고도
상승에
따른
풍력밀도
증가추세가
동일하게
표현되
기가
1.07
분석되어
체계적인
유사성이
인되
.
(3)
스위스
S&P
풍력밀도의
경우
KIER
와의
상관성이
R
2
=
0.82(
육상
), 0.87(
해상
)
3TIER
R
2
=0.57(
육상
)
비하여
44%
높은
것으로
분석되
.
그러나
풍속은
KIER
대비
30%
과대예측할
아니라
와이블
형상계수
바이어스도
+0.5
.
연직방향에
대한
비교분석을
통하여는
풍속분포지수의
상관도가
비선형적인
보였다
.
결론적으로
S&P
해석
모형에
대한
재검토가
요할
것으로
판단된다
.
상용
풍력자원지도의
경우
공간해상도에
따라
풍력자원
포에
대한
력이
우되며
,
따라서
공간해상도는
가격과
된다
.
그러나
고해상도가
정확도의
향상으로
이어진다고
들며
,
본질적으로
해석과에
체계적인
기상통계학적
성이
표현되어야
것이다
.
이러한
측면에서
연구의
비교분
석은
풍력자원지도의
신뢰도를
평가할
있는
하나의
체계적
방법
제시하였다고
사료된다
.
감사의
연구는
한국에너지기술연구원
요사업으로
수행한
입니다
(GP2014-0030).
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... 그러나 바람은 국지적으로 지형학 적 요소에 의한 다변성이 존재하기 때문에 바람의 시 공간적 특징을 정확하게 진단하고 평가하는 것은 매우 어렵고 (5,6) , 심지어 대기 대순환에 의한 기후학적 계절 풍 등에 영향을 받으며 지표-대기 상호작용 및 열과 수 증기 수송 등에 관여하는 중요한 기후 시스템의 요소 이기 때문에 지구온난화와 기후변화에 의한 영향도 무 시할 수 없다 (7)(8)(9) . 이에 따라, 지금까지 바람의 기상학 적 시공간 특성 파악 및 기후학적 영향평가를 위한 다 양한 노력이 시도되었으며, 신재생에너지 자원의 측면 에서도 전 세계적으로 풍력발전소 부지선정의 타당성 평가 및 바람자원의 효율적 이용과 경제성 평가를 위 한 풍력자원지도의 생산 등 여러 연구가 수행되어져 왔다 (5)(6)(7)(8)(9)(10)(11)(12)(13)(14) . 그럼에도 (9) . ...
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... PCA로 분석한 DTM의 주성분 PC1, PC2, PC3는 각각 진동제 어(vibration control), 공기역학/교량(aerodynamics/bridge), 고 층건물(high-rise building)로 나타났으며, 이들의 설명력은 5.2% 6.8%이다. (22) Topic 7은 풍력자원평가(wind resource assessment)와 (23,24) 바 람지도(wind map)가 (25,26) 핵심 키워드이며, Topic 8은 건물진 동의 능동제어가 (27,28) 핵심 키워드이다. ...
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... To improve the accuracy of KIER-WindMap, observation data (AWS/ASOS, Sonde/Wind profiler, Buoy) of KMA and related institutions were assimilated into the background field using the fourdimensional data assimilation technique. The accuracy of the final wind resource map was proven through various verification studies [16,17]. ...
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