The impact of large scale atmospheric circulation patterns on wind power generation and its potential predictability: A case study over the UK
The impact of large scale atmospheric circulation patterns on wind power generation and its potential predictability: A case study over the UK
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DOI：
10.1016/j.renene.2011.01.025
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发表时间：
2011-08-01
期刊：
影响因子：
8.7
通讯作者：
Methven, John
中科院分区：
文献类型：
--
作者：
Brayshaw, David James;Troccoli, Alberto;Methven, John
近年来，可再生能源发电技术的部署越来越多，特别是大型风力发电场。随着风电场部署的增加，重要的是要很好地了解所产生的能源如何受到气候变化的影响，在很宽的时间范围内，从短期到长期，（小时至周）至长通过将英国特定地点的风速与大尺度气候模式联系起来，（北大西洋振荡或“NAO”），计算在三种不同NAO状态下由建模的风力涡轮机产生的功率。结果发现，在这些NAO状态下的风条件可能会产生高达10%的平均风力输出的差异。一个简单的模型被用来证明未来NAO状态的预测可以潜在地用于改进月平均风力发电量的月前统计预测。结果证实，NAO对小时，涡轮机的日平均和月平均功率输出分布，对（a）气象数据的使用具有重要意义（例如，它们与大尺度气候模式的关系），以及（B）利用季节性到十年期气候预测来估计未来风电场的功率输出。这表明，进一步研究大规模气候变化与风力发电之间的联系既有必要，也有价值。(C)2011爱思唯尔有限公司版权所有。
Over recent years there has been an increasing deployment of renewable energy generation technologies, particularly large-scale wind farms. As wind farm deployment increases, it is vital to gain a good understanding of how the energy produced is affected by climate variations, over a wide range of time-scales, from short (hours to weeks) to long (months to decades) periods.By relating wind speed at specific sites in the UK to a large-scale climate pattern (the North Atlantic Oscillation or "NAO"), the power generated by a modelled wind turbine under three different NAO states is calculated. It was found that the wind conditions under these NAO states may yield a difference in the mean wind power output of up to 10%. A simple model is used to demonstrate that forecasts of future NAO states can potentially be used to improve month-ahead statistical forecasts of monthly-mean wind power generation.The results confirm that the NAO has a significant impact on the hourly-, daily- and monthly-mean power output distributions from the turbine with important implications for (a) the use of meteorological data (e.g. their relationship to large-scale climate patterns) in wind farm site assessment and, (b) the utilisation of seasonal-to-decadal climate forecasts to estimate future wind farm power output. This suggests that further research into the links between large-scale climate variability and wind power generation is both necessary and valuable. (C) 2011 Elsevier Ltd. All rights reserved.