%0 Journal Article
%T An Integrated and Revised Method of Forecasting Wind Speed for Wind Farms<br>风电场风速预报集合订正方法的尝试性研究
%A JIANG Ying
%A SONG Lili
%A CHENG Xinghong
%A <br>江滢
%A 宋丽莉
%A 程兴宏
%J 资源科学
%D 2013
%I 
%X Many statistical revised methods have been used in wind speed or wind power forecasting systems and research. However, these statistical methods have their own advantages. In this paper, an integrated and revised concept has been used which is more advanced and mostly used in weather forecasting. The revised test was done on wind speed for wind farms based on the observed wind speed and the forecast wind speed, temperature, air pressure, and wind direction from wind power forecasting system (WINPOP). Test methods included BP neural network, adaptive least square method and integrated methods. Test time: 1 March to 30 June 2012. Time resolution: every 15 minutes. Test place: HYZ wind farm and GHK wind farm in Gansu. Our results showed that wind speed forecasting by every single revised method is better than that of WINPOP and the error was reduced to 19.6%~30.8% and 23.4%~31.0% than that of WINPOP. The revised method error was 77%~93% and 78%~88% less than that of WINPOP for future 24 hours forecasting at HYZ and GHK. The error of integrated revised forecasting is less than that of WINPOP and every single revised forecasting. Error from the integrated revised method decreased to 40.5% and 36.8% and the percentage increased to 94% and 90% of revised error less than that of WINPOP on HYZ and GHK, respectively. Both the integrated method and single revised method remove system error of WINPOPPO remarkably. The integrated method can also remove daily variation error of WINPOP. There were no obvious changes for wind speed forecast error with prediction time increasing from 24h to 72h. The forecast error showed a decreasing trend for wind speed at(0~5)m/s and then increased for wind speeds greater than 5m/s.
%K Wind farms
%K Wind speed
%K Forecast
%K Integrated revised
%K Gansu Province<br>风电场
%K 风速
%K 预报
%K 集合订正
%K 甘肃省
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=B5EDD921F3D863E289B22F36E70174A7007B5F5E43D63598017D41BB67247657&cid=B47B31F6349F979B&jid=9DEEAF23637E6E9539AD99BE6ABAB2B3&aid=D096FE55569F2801C5CFF1FCD3414B2F&yid=FF7AA908D58E97FA&vid=6209D9E8050195F5&iid=38B194292C032A66&sid=B28C697BC3A1BA62&eid=34D13857B558254E&journal_id=1007-7588&journal_name=资源科学&referenced_num=0&reference_num=23