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제주지역 바람자료 분석 및 풍속 예측에 관한 연구

A Study on the Wind Data Analysis and Wind Speed Forecasting in Jeju Area

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주제분류기타공학

초록

In this study, we analyzed the characteristics of wind speed and wind direction at different locations in Jeju area using past 10 years observed data and used them in our wind power forecasting model. Generally the strongest hourly wind speeds were observed during daytime(13KST∼15KST) whilst the strongest monthly wind speeds were measured during January and February. The analysis with regards to the available wind speeds for power generation gave percentages of 83%, 67%, 65% and 59% of wind speeds over 4m/s for the locations Gosan, Sungsan, Jeju site and Seogwipo site, respectively. Consequently the most favorable periods for power generation in Jeju area are in the winter season and generally during daytime. The predicted wind speed from the forecast model was in average lower(0.7m/s) than the observed wind speed and the correlation coefficient was decreasing with longer prediction times (0.84 for 1h, 0.77 for 12h, 0.72 for 24h and 0.67 for 48h). For the 12hour prediction horizon prediction errors were about 22∼23%, increased gradually up to 25∼29% for 48 hours predictions.

Abstract

In this study, we analyzed the characteristics of wind speed and wind direction at different locations in Jeju area using past 10 years observed data and used them in our wind power forecasting model. Generally the strongest hourly wind speeds were observed during daytime(13KST∼15KST) whilst the strongest monthly wind speeds were measured during January and February. The analysis with regards to the available wind speeds for power generation gave percentages of 83%, 67%, 65% and 59% of wind speeds over 4m/s for the locations Gosan, Sungsan, Jeju site and Seogwipo site, respectively. Consequently the most favorable periods for power generation in Jeju area are in the winter season and generally during daytime. The predicted wind speed from the forecast model was in average lower(0.7m/s) than the observed wind speed and the correlation coefficient was decreasing with longer prediction times (0.84 for 1h, 0.77 for 12h, 0.72 for 24h and 0.67 for 48h). For the 12hour prediction horizon prediction errors were about 22∼23%, increased gradually up to 25∼29% for 48 hours predictions.

참고문헌 (8)

  1. , 기상청[URL]
  2. 제주지방기상청, "제주지방예보실무지침서", ~ (2008)
  3. 김경보, "KWRF를 이용한 풍력발전 출력 예측 타당성 연구", 춘계학술발표회 (2008), 한국풍력에너지학회
  4. 이영미, "풍력발전량 예측시스템 개발을 위한 기상예보 시스템 구축", 춘계학술발표회 (2008), 한국풍력에너지학회
  5. [URL]
  6. Wicker,L.J, "Time splitting methods for elastic models using forward time schemes", Wea. Rev, 130, pp.2088~2097 (2002)
  7. "User's Guide for Advanced Research WRF (ARW) Modeling System Version", ~
  8. 김현구, "월령단지 풍력발전 예보모형 개발에 관한 연구", 한국태양에너지학회 논문집, 26(2), pp.27~34 (2006), 한국태양에너지학회

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