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Very short-term wind speed forecasting with Bayesian structural break model

机译:利用贝叶斯结构折断模型进行短期风速预测

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摘要

This paper examines a new time series method for very short-term wind speed forecasting. The time series forecasting model is based on Bayesian theory and structural break modeling, which could incorporate domain knowledge about wind speed as a prior. Besides this Bayesian structural break model predicts wind speed as a set of possible values, which is different from classical time series model's single-value prediction This set of predicted values could be used for various applications, such as wind turbine predictive control, wind power scheduling. The proposed model is tested with actual wind speed data collected from utility-scale wind turbines.
机译:本文研究了一种用于短期风速预测的新时间序列方法。时间序列预测模型基于贝叶斯理论和结构折断模型,可以将关于风速的领域知识作为先验。除了此贝叶斯结构折断模型之外,将风速作为一组可能的值进行预测,这与经典时间序列模型的单值预测不同。该组预测值可用于各种应用,例如风力涡轮机的预测控制,风力发电调度。使用从公用事业规模的风力涡轮机收集的实际风速数据对提出的模型进行了测试。

著录项

  • 来源
    《Renewable energy》 |2013年第2期|637-647|共11页
  • 作者单位

    School of Business, Nanjing University, 22 Hankou road, Nanjing 210093, China;

    School of Business, Nanjing University, 22 Hankou road, Nanjing 210093, China;

    Department of Mechanical and Industrial Engineering, 3131 Seamans Center, The University of Iowa, IA 52242-1527, Iowa City, United States;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    time series; forecasting; wind power; wind speed; bayesian structural break model;

    机译:时间序列;预测;风力;风速;贝叶斯结构破坏模型;

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