Interpolation of missing wind data based on ANFIS |
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| Authors: | Zhiling Yang Yongqian Liu Chengrong Li |
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| Affiliation: | 1. Energy & Power Engineering School, North China Electric Power University, Beijing 102206, China;2. Renewable Energy School, North China Electric Power University, Beijing 102206, China;3. Electrical & Electronic Engineering School, North China Electric Power University, Beijing 102206, China |
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| Abstract: | 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. |
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