지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
오류제보하기
Long-term time series of wind data are essential to estimate the control and output performance of wind turbine systems. In this work, we propose and verify the use of Markov chains to generate long-term synthetic wind data using measured data at Wido Island. We first identify the Weibull distribution, the daily and monthly wind speed variations of the Wido region. Statistical parameters of the synthetic wind data such as maximum wind speed, minimum wind speed, average wind speed, and standard deviation are compared with those of observed data via met mast. In addition, both plots of autocorrelation and histogram are examined to verify the coincidence between synthetic and observed wind data. The transition matrix reflects the characteristics of wind speed variations over time at the measured site. A cumulative state transition matrix is obtained from the state transition matrix to determine the next state with a random number generator. The size of the synthetic wind data was iteratively determined to minimize statistical parameter errors. Through this study, long-term synthetic wind data can be adopted to simulate both the control performance and capacity factor of wind turbine systems scheduled to be installed in the site of interest.
목차
등록된 정보가 없습니다.
참고문헌 (8)
참고문헌 신청
Balzter, H. / 2000 / Markov chain models for vegetation dynamics / Ecological Modelling 126:139~154
Srikanthan, R. / 2001 / Stochastic generation of annual, monthly and daily climate data: a review / Hydrology and Earth System Sciences 5(4):653~670
Balouktsis, A. / 1986 / Stochastic simulation of hourly and daily average wind speed sequences / Wind Engineering 10(1):1~11
Poggi, P. / 2000 / Stochastic study of hourly total solar radiation in Corsica using a Markov model / Int. J. of Climatology 20:1843~1860
Lei, M. / 2009 / A review on the forecasting of wind speed and generated power / Renewabe and Sustainable Energy 13(4):915~920
Srikanthan, R. / 2001 / Stochastic generation of annual, monthly and daily climate data: a review / Hydrology and Earth System Sciences 5(4):653~670
Balouktsis, A. / 1986 / Stochastic simulation of hourly and daily average wind speed sequences / Wind Engineering 10(1):1~11
Poggi, P. / 2000 / Stochastic study of hourly total solar radiation in Corsica using a Markov model / Int. J. of Climatology 20:1843~1860
Lei, M. / 2009 / A review on the forecasting of wind speed and generated power / Renewabe and Sustainable Energy 13(4):915~920
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