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Interpolation of missing wind data based on ANFIS

机译:基于ANFIS的风数据缺失插值

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摘要

Measured wind data is one of the key input data for wind farm planning and design. There are always some missing and invalid data in wind measurement, which poses the main challenges for wind energy resources assessment. In this paper, the rules of integrity check and reasonableness check are introduced, then an adaptive neuro-fuzzy inference system (ANFIS) model is proposed, in which fuzzy inference algorithm are used to interpolate the missing and invalid wind data. A further comparison and analysis is given between the calculating result and measured data. Meanwhile Using methods of wind shear coefficient and ANFIS, 12 measured wind data sets from a wind farm in North China are interpolated and analyzed, respectively. The results proved the effectiveness of ANFIS.
机译:测得的风能数据是风电场规划和设计的关键输入数据之一。风量测量中总是存在一些缺失和无效的数据,这对风能资源评估提出了主要挑战。本文介绍了完整性检查和合理性检查的规​​则,然后提出了一种自适应神经模糊推理系统(ANFIS)模型,其中使用模糊推理算法对缺失和无效的风数据进行插值。对计算结果与实测数据进行了进一步的比较分析。同时,利用风切变系数和ANFIS方法,分别对来自华北某风电场的12个实测风数据集进行插值和分析。结果证明了ANFIS的有效性。

著录项

  • 来源
    《Renewable energy》 |2011年第3期|p.993-998|共6页
  • 作者单位

    Energy & Power Engineering School, North China Electric Power University, Beijing 102206, China;

    Renewable Energy School, North China Electric Power University, Beijing 102206, China;

    Electrical & Electronic Engineering School, North China Electric Power University, Beijing 102206, China;

  • 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

    data interpolation; fuzzy inference; ANFIS; measured wind data;

    机译:数据插值;模糊推理ANFIS;测风数据;
  • 入库时间 2022-08-18 00:26:29

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