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文章摘要
基于时间序列的多采样尺度风电功率多步预测研究
Study on Multi Sampling Scale Multi-step Wind Power Prediction Based on Time Series Method
Received:July 10, 2014  Revised:July 10, 2014
DOI:
中文关键词: 风电功率  周期分量  建模域均值法  时间序列  多采样尺度
英文关键词: wind  power, periodic  component, mean  method of  modeling domain, time  series, multi  sampling scale
基金项目:国家重点基础研究发展计划项目(973计划) (2013CB228201);国家自然科学基金(51307017);吉林省科技发展计划项目(20140520129JH);吉林省教育厅“十二五”科学技术研究项目(吉教科合字[2014]第474号);吉林市科技发展计划资助项目(2013625004)
Author NameAffiliationE-mail
YANG Mao* School of Electrical Engineering,Northeast Dianli University yangmao820@163.com 
SUN Yong School of Electrical Engineering,Northeast Dianli University  
WANG Dong State Grid Beijing Electric Power Company  
MU Gang School of Electrical Engineering,Northeast Dianli University  
ZHANG Ming-ming Tianjin SDIC Jinneng Electric Power co.LTD  
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中文摘要:
      风力发电联网运行是实现风能大规模开发利用的主要途径,准确的风电功率实时预测是实现风能大规模合理调度的有效手段。本文建立了基于时间序列的多采样尺度风电功率多步预测模型。对于周期分量利用建模域均值法进行预测,剩余分量通过平稳性检验后利用多采样尺度时间序列法进行预测。利用两个不同风场的实测风电功率数据,进行不同时间段的实时预测,与持续法和时间序列法的滚动预测模型相比,该预测模型能有效地提高预测精度。
英文摘要:
      Wind power generation with network running is the main way to realize the exploitation and utilization of wind energy in large-scale. Accurate real-time prediction of wind power is an effective means to achieve rational management of wind energy in large-scale. A multi sampling scale multi-step prediction model based on time series method is established for wind power. For the periodic component, mean method of modeling domain is adopted to predict; For the remaining component, multi sampling scale multi-step prediction model based on time series method is adopted to predict after stationarity test. By means of the measured dates of two different wind farms, we perform the wind power prediction in real-time at different times, the prediction results show the effectiveness of the prediction model compare with the methods of persistence and rolling multi-step model based on time series method.
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