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《Journal of North China Electric Power University(Natural Science Edition)》 2008-03
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Application study of three methods in wind speed prediction

HAN Shuang,YANG Yong-ping,LIU Yong-qian(School of Energy and Power Engineering,North China Electric Power University,Beijing 102206,China)  
The comparison of persistence,ARIMA and BP neural network methods in wind speed prediction application of 1h in advance was discussed.To avoid the seasonality influence,models were built respectively for every calendar month.Wind speed was a non-stationary sequence and difference algorithm should be used for original wind speed sequence.The input nerve cells number was decided through relativity analysis for sample data.The result shows that ARIMA model and BP network model are better than persistence method and BP better than ARIMA under most circumstances.But there are examples that persistence method is better than ARIMA and BP models and ARIMA better than BP model.It is improper to say that one method is always superior to another;to choose proper prediction method for the best prediction,detailed analysis should be made.
【Fund】: 国家高技术研究发展计划(863计划)资助项目(2007AA05Z428)
【CateGory Index】: P457.5
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【Secondary References】
Chinese Journal Full-text Database 4 Hits
1 PENG Huai-wu1, YANG Xiao-feng1, LIU Fang-rui2 (1. Inner Mongolia Power Exploration & Design Institute, Huhhot 010020, Inner Mongolia Autonomous Region, China; 2. College of Electrical & Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei Province, China);Short-Term Wind Speed Forecasting of Wind Farm Based on SVM Method[J];Power System and Clean Energy;2009-07
2 TANG Fan,LIU Tian-qi,LI Xing-yuan(School of Electrical Engineering and Information,Sichuan University,Chengdu 610065,Sichuan Province,China);Simulation of Flywheel Energy Storage System for Power Control in Wind Farms[J];Power System and Clean Energy;2010-02
3 GAO Yang1,CHEN Hua-yu2,OU Yang-qun3(1.Shenyang Institute of Engineering,Shenyang 110136,Liaoning Province,China;2.CPI Northeast Power Company Limited,Shenyang 110017,Liaoning Province,China;3.Liaoning Electric Power Company Limited,Shenyang 110006,Liaoning Province,China);A Summery of Studies on Wind Power Prediction Technologies[J];Power System and Clean Energy;2010-04
4 LIU Ye,LU Xiao-fen,FANG Rui-ming,SONG Yan-bing(Huaqiao University,Quanzhou 362021,Fujian Province,China);A Review on Wind Speed Forecast Methods in Wind Power System[J];Power System and Clean Energy;2010-06
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