Quantifying the variability of wind energy

被引:34
|
作者
Watson, Simon [1 ]
机构
[1] Univ Loughborough, Ctr Renewable Energy Syst Technol, Sch Elect Elect & Syst Engn, Loughborough LE67 5AH, Leics, England
基金
英国工程与自然科学研究理事会;
关键词
CLIMATE-CHANGE IMPACTS; PROBABILITY-DISTRIBUTION; POWER RESOURCES; OFFSHORE WIND; SURFACE WINDS; SPEED; TRENDS; DISTRIBUTIONS; VULNERABILITY; STATISTICS;
D O I
10.1002/wene.95
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Wind by its very nature is a variable element. Its variation is different on different timescales and spatially its magnitude can change dramatically depending on local climatology and terrain. This has implications in a variety of sectors, not least in the wind energy sector. The accuracy of weather forecasting models has increased significantly in the last few decades and these models are able to give an insight into variability on the hourly and daily timescales. On shorter timescales, predicting chaotic turbulent fluctuations is far more challenging. Similarly, the ability to make seasonal forecasts is extremely limited. General circulation models (GCMs) can give insights into possible future decadal fluctuations, but there are still large uncertainties. Observational data can give useful information concerning variation on a variety of timescales, but data quality and spatial coverage can be variable. An understanding of local scale spatial variations in wind is extremely important in wind farm siting. In the last 40 years, there have been significant advances in predicting these variations using computer models, although there remain significant challenges in understanding the behavior of the wind in certain environments. Both the spatial and temporal variations of wind are important considerations when wind power is integrated into electricity networks, and this will become an ever more important consideration as wind generation makes an increasing contribution to our global energy needs. (C) 2013 John Wiley & Sons, Ltd.
引用
收藏
页码:330 / 342
页数:13
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