Offshore Wind Speed Forecasting: The Correlation between Satellite-Observed Monthly Sea Surface Temperature and Wind Speed over the Seas around the Korean Peninsula

Jin-Young Kim, Hyun-Goo Kim and Yong-Heack Kang
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Jin-Young Kim: New & Renewable Energy Data Center, Korea Institute of Energy Research, 152 Gajeong-ro, Yuseong-gu, Daejeon 34129, Korea
Hyun-Goo Kim: New & Renewable Energy Data Center, Korea Institute of Energy Research, 152 Gajeong-ro, Yuseong-gu, Daejeon 34129, Korea
Yong-Heack Kang: New & Renewable Energy Data Center, Korea Institute of Energy Research, 152 Gajeong-ro, Yuseong-gu, Daejeon 34129, Korea

Energies, 2017, vol. 10, issue 7, 1-15

Abstract: Wind power forecasting is a key role for large-scale wind power penetration on conventional electric power systems by understanding stochastic nature of winds. This paper proposes an empirical statistical model for forecasting monthly offshore wind speeds as a function of remotely sensed sea surface temperatures over the seas around the Korean Peninsula. The model uses the optimal lagged multiple linear regression method, and predictors are characterized by mixed periodicities derived from the autocorrelation between spatially variable satellite-observed sea surface temperatures and wind speeds at all grid points over a period of about ten years (2001 to 2008). Offshore wind speeds were found to be correlated with sea surface temperatures within a seasonal range of two- to four-month lags. In particular, offshore wind speeds were closely associated with the sea surface temperature at lag 4 M, followed by lag 3 M and lag 2 M. Correlation is less at lag 1 M as compared lag 2 M, lag 3 M and lag 4 M. The results demonstrate that this approach successfully produces accurate depictions of monthly wind speeds at the gridded network. The hindcast offshore wind speeds and wind power density showed slightly improved skills compared to the seasonally varying climatology with the value of root-mean square errors, +18% and +23%, respectively. The spatial distributions of the monthly gridded wind speed and wind power density remained fairly stable from one month to another, whereas individual regions displayed slight differences in variability. The results of this study are expected to be useful in establishing guidelines for operating and managing nascent offshore farms around the Korean Peninsula.

Keywords: offshore wind speed forecasting; correlation; monthly wind speed; sea surface temperature; satellite; statistical approach; multiple linear regression model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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