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Analysis on Application of Wavelet Neural Network in Wind Electricity Power Prediction

机译:小波神经网络在风电预测中的应用分析

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Wind electricity power has fluctuation, and accurate and reasonable wind electricity power prediction is very important for solving wind electricity network and combination. This paper takes an analysis of a lot of actual data of a certain wind electricity field. Through wavelet neural network and time series method rolling, it can predict the overall power of wind electricity field. The result shows that for the original data of sampling time length and large sampling frequency, the model constructed by this paper has very good prediction effect. Because of the fan installation position, wind electricity fan flow effect and other random factor influence, wind electricity field overall power and single unit power distribution have difference. Through comparing with the time series parameters, it puts forward that single wind electricity unit power has smooth effect for overall power of wind electricity field. Finally, it summarizes the prediction effect and puts forward some reasonable suggestions for wind electricity network problems.
机译:风电力具有波动,准确且合理的风电力预测对求解风电网和组合非常重要。本文对某种风电场的许多实际数据进行了分析。通过小波神经网络和时间序列方法滚动,它可以预测风电场的整体力量。结果表明,对于采样时间长度和大的采样频率的原始数据,本文构造的模型具有非常好的预测效果。由于风扇安装位置,风电风扇流动效果等随机因子影响,风电场总功率和单位配电有差异。通过与时间序列参数进行比较,它提出了单风电机电源对风电场的整体力量具有平稳效果。最后,它总结了预测效应,并提出了对风电网问题的一些合理建议。

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