해양환경안전학회지 (Journal of the Korean Society of Marine Environment & Safety)

  • 제18권6호
  • /
  • Pages.545-550
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  • 2012
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  • 1229-3431(pISSN)
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  • 2287-3341(eISSN)
해양환경안전학회 (The Korean Society of Marine Environment and safety)
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제주도 북동부 한동지역의 MCP 회귀모델식을 적용한 AEP계산에 대한 연구

Estimation of Annual Energy Production Based on Regression Measure-Correlative-Predict at Handong, the Northeastern Jeju Island

  • 고정우 (제주대학교 대학원 풍력특성화 협동과정) ;
  • 문서정 (제주대학교 대학원 풍력특성화 협동과정) ;
  • 이병걸 (제주대학교 해양과학대학 토목공학과)
  • Ko, Jung-Woo (Department of Civil Engineering, Jeju National University Graduate School of Specialized Wind Energy) ;
  • Moon, Seo-Jeong (Department of Civil Engineering, Jeju National University Graduate School of Specialized Wind Energy) ;
  • Lee, Byung-Gul (Department of Civil Engineering, Jeju National University College of Ocean Science)
  • 투고 : 2012.11.26
  • 심사 : 2012.12.27
  • 발행 : 2012.12.31
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초록

풍력발전 단지의 설계시 풍력 자원 평가 과정은 필수적인 과정이다. 풍력 자원 평가를 위해 장기풍황(20년)자료를 이용하여야 하지만 장기간 관측하는 것은 어렵기 때문에 예정지의 1년 이상의 관측데이터로 평가를 실시하였다. 예정지의 단기 풍황탑(Met-Mast; Meteorology Mast) 자료를 주변의 장기관측 자료인 자동기상관측(AWS; Automatic Weather Station)데이터를 이용하여 수학적 보간법으로 예정지의 데이터를 장기 데이터로 변환한 것을 MCP(Measure-Correlative-Predict)기법이라 한다. 본 연구에서는 MCP기법 중 선형 회계방법을 적용하였다. 선택된 MCP 회귀 모델식에 따라 제주 북동부 구좌지역의 AWS데이터를 제주 북동부 한동 지역의 Met-mast 데이터에 적용하여 연간 에너지 생산량을 예측 하였다. 예정지의 단기 풍황을 이용하였을 때와 보정된 장기 풍황을 이용하여 때 연간 에너지 생산량을 비교하였다. 그 결과 연간 약 3.6 %의 예측오차를 보였고, 이는 연간 약 271 MW의 에너지 생산량의 차이를 의미한다. 풍력발전기의 생애주기인 20년을 비교 하였을 때 약 5,420 MW의 차이를 나타내었으며, 이는 약 9개월 정도의 에너지 생산량과 비슷한 수준이다. 결과적으로, 제안 된 선형 회귀 MCP 방법을 이용하는 것이 단기관측 자료를 통한 불확식성을 제거하는 합리적인 방법으로 판단된다.

Wind resource assessment is necessary when designing wind farm. To get the assessment, we must use a long term(20 years) observed wind data but it is so hard. so that we usually measured more than a year on the planned site. From the wind data, we can calculate wind energy related with the wind farm site. However, it calculate wind energy to collect the long term data from Met-mast(Meteorology Mast) station on the site since the Met-mast is unstable from strong wind such as Typhoon or storm surge which is Non-periodic. To solve the lack of the long term data of the site, we usually derive new data from the long term observed data of AWS(Automatic Weather Station) around the wind farm area using mathematical interpolation method. The interpolation method is called MCP(Measure-Correlative-Predict). In this study, based on the MCP Regression Model proposed by us, we estimated the wind energy at Handong site using AEP(Annual Energy Production) from Gujwa AWS data in Jeju. The calculated wind energy at Handong was shown a good agreement between the predicted and the measured results based on the linear regression MCP. Short term AEP was about 7,475MW/year. Long term AEP was about 7,205MW/year. it showed an 3.6% of annual prediction different. It represents difference of 271MW in annual energy production. In comparison with 20years, it shows difference of 5,420MW, and this is about 9 months of energy production. From the results, we found that the proposed linear regression MCP method was very reasonable to estimate the wind resource of wind farm.

키워드

참고문헌

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피인용 문헌

  1. A Study on a Wind Turbine Data Logger System based on WiFi for Meteorological Resource Measurement vol.10, pp.1, 2015, https://doi.org/10.13067/JKIECS.2015.10.1.55
  2. Remote Sensing 기술을 활용한 제주 북동부 지역의 풍력자원 예측의 정확성 향상에 대한 연구 vol.30, pp.4, 2012, https://doi.org/10.5322/jesi.2021.30.4.335