%0 Journal Article %1 Brayshaw2011Impact %A Brayshaw, David J. %A Troccoli, Alberto %A Fordham, Rachael %A Methven, John %D 2011 %J Renewable Energy %K energy renewables wind %N 8 %P 2087--2096 %R 10.1016/j.renene.2011.01.025 %T The impact of large scale atmospheric circulation patterns on wind power generation and its potential predictability: A case study over the UK %U http://dx.doi.org/10.1016/j.renene.2011.01.025 %V 36 %X 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. ► Power output from wind turbines is sensitive to wind speed. ► The affect of large-scale atmospheric circulation (NAO) on UK wind is investigated. ► Slow (monthly) changes in NAO state are shown to affect turbine output by up to 10\%. ► Monthly turbine power output forecasts are improved using simple NAO predictions.

@article{Brayshaw2011Impact, abstract = {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. \^{a}–º Power output from wind turbines is sensitive to wind speed. \^{a}–º The affect of large-scale atmospheric circulation (NAO) on UK wind is investigated. \^{a}–º Slow (monthly) changes in NAO state are shown to affect turbine output by up to 10\%. \^{a}–º Monthly turbine power output forecasts are improved using simple NAO predictions.}, added-at = {2018-06-18T21:23:34.000+0200}, author = {Brayshaw, David J. and Troccoli, Alberto and Fordham, Rachael and Methven, John}, biburl = {https://www.bibsonomy.org/bibtex/2d1a607512ab6910c4e987122eacfb810/pbett}, citeulike-article-id = {8888288}, citeulike-attachment-1 = {Brayshaw2011rene1.pdf; /pdf/user/pbett/article/8888288/878602/Brayshaw2011rene1.pdf; 1b89afe49f4f6d90a12aad5f9dc325bb6abd7ef0}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.renene.2011.01.025}, day = 24, doi = {10.1016/j.renene.2011.01.025}, file = {Brayshaw2011rene1.pdf}, interhash = {948515da61f5a0a42a99b7e9fd012c1b}, intrahash = {d1a607512ab6910c4e987122eacfb810}, issn = {09601481}, journal = {Renewable Energy}, keywords = {energy renewables wind}, month = aug, number = 8, pages = {2087--2096}, posted-at = {2011-11-14 14:53:21}, priority = {2}, timestamp = {2019-02-22T16:49:39.000+0100}, title = {The impact of large scale atmospheric circulation patterns on wind power generation and its potential predictability: A case study over the UK}, url = {http://dx.doi.org/10.1016/j.renene.2011.01.025}, volume = 36, year = 2011 }