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Spatial and Temporal Patterns of Global Onshore Wind Speed Distribution

Journal Article · · Environmental Research Letters, 8(3):Article No. 034029
Wind power, a renewable energy source, can play an important role in electrical energy generation. Information regarding wind energy potential is important both for energy related modeling and for decision-making in the policy community. While wind speed datasets with high spatial and temporal resolution are often ultimately used for detailed planning, simpler assumptions are often used in analysis work. An accurate representation of the wind speed frequency distribution is needed in order to properly characterize wind energy potential. Using a power density method, this study estimated global variation in wind parameters as fitted to a Weibull density function using NCEP/CFSR reanalysis data. The estimated Weibull distribution performs well in fitting the time series wind speed data at the global level according to R2, root mean square error, and power density error. The spatial, decadal, and seasonal patterns of wind speed distribution were then evaluated. We also analyzed the potential error in wind power estimation when a commonly assumed Rayleigh distribution (Weibull k = 2) is used. We find that the assumption of the same Weibull parameter across large regions can result in substantial errors. While large-scale wind speed data is often presented in the form of average wind speeds, these results highlight the need to also provide information on the wind speed distribution.
Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC05-76RL01830
OSTI ID:
1094955
Report Number(s):
PNNL-SA-92908; KP1703020
Journal Information:
Environmental Research Letters, 8(3):Article No. 034029, Journal Name: Environmental Research Letters, 8(3):Article No. 034029
Country of Publication:
United States
Language:
English

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