MCP방법을 이용한 장기간 풍속 및 풍력에너지 변동 특성 분석
Variability Characteristics Analysis of the Long-term Wind and Wind Energy Using the MCP Method
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참고문헌
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초록
Wind resource data of short-term period has to be corrected a long-term period by using MCP method that Is a statistical method to predict the long-term wind resource at target site data with a reference site data. Because the field measurement for wind assessment is limited to a short period by various constraints. In this study, 2 different MCP methods such as Linear regression and Matrix method were chosen to compare the predictive accuracy between the methods. Finally long-term wind speed, wind power density and capacity factor at the target site for 20 years were estimated for the variability of wind and wind energy. As a result, for 20 years annual average wind speed, Yellow sea off shore wind farm was estimated to have 4.29% for coefficient of variation, CV, and-9.57%〜9.53% for range of variation, RV. It was predicted that the annual wind speed at Yellow sea offshore wind farm varied within±10%.
Abstract
Wind resource data of short-term period has to be corrected a long-term period by using MCP method that Is a statistical method to predict the long-term wind resource at target site data with a reference site data. Because the field measurement for wind assessment is limited to a short period by various constraints. In this study, 2 different MCP methods such as Linear regression and Matrix method were chosen to compare the predictive accuracy between the methods. Finally long-term wind speed, wind power density and capacity factor at the target site for 20 years were estimated for the variability of wind and wind energy. As a result, for 20 years annual average wind speed, Yellow sea off shore wind farm was estimated to have 4.29% for coefficient of variation, CV, and-9.57%〜9.53% for range of variation, RV. It was predicted that the annual wind speed at Yellow sea offshore wind farm varied within±10%.
참고문헌 (11)
- Hyun-gu Kim, "Analysis of Wind Shear Patterns and Application of Measure- Correlate-Predict at Pohang Region", Journal of The Korean Society for New and Renewable Energy, 1(2) (2004)
- Walmsley, J. L., "A method of correlating wind data between two station with application to the Alberta Oil Sands, Atmos", Ocean, 16 (1978)
- An Application of MCP Technique to Jeju Island, "Gyeong-il Kwak", WWEC, ~ (2009)
- A Derrick, "Development of the measure- correlate-Predict stratrgy for site assessment", Proceedings of the BWEA (1992)
- J. C. Wood, "A new matrix method of predicting long-term wind roses with MCP", Journal of Wind Engineering and Industrial Aerodynamics, 66 (1997)
- P. E. J. Vermeulen, "Application of matrix MCP analysis in mountainous Armenia", Proceedings of the EWEA (2001)
- E. Sreevalsan, "Wind Farm Site Assessment Using Measure-Correlate -Predict(MCP) Analtsis", Wind Enginering, 31(2) (2007)
- Anthony L. Roger, "Comparison of the performance of four measure-correlate-predict algorithms", Journal of Wind Engineering and Industrial Aerodynamics, 93 (2005)
- A Study on the Demonstration Project for 2.5 GW Offshore Wind Farm of the Southern part of Yellow Sea(Resource Analysis and Wind Farm Development), "Moon-Seok, Jang", KIER, ~ (2012)
- 고경남, "Prediction of long-term wind speed and capacity factor using Measure-Correlate-Predict method", 한국태양에너지학회 논문집, 32(6), pp.37~43 (2012), 한국태양에너지학회
- Nakao T, "Characteristic on the wind variability for the planning of wind turbine generation systems", Journal of the Japan Wind Energy Association, 28(4) (2004)