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Wind power prediction using EMoFS technique

机译:使用EMoFS技术的风电功率预测

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摘要

It is crucial for the energy market to predict the generated wind power of a wind park one day ahead. However, the error rate of the wind power prediction is high due to i) the natural fact that the behaviour of wind is stochastic, non-stationary and intermittent, ii) the fact that the relation between produced wind power and instant wind speed is nonlinear. In this study, a novel approach that is utilizing EMoFS technique in wind power prediction is proposed. In order to verify the validity of the proposed approach, error rate of the predictions of the proposed approach is compared with the ones that are generated by artificial neural networks based approach. It is observed that the proposed approach generates slightly better results compared to the generic approach that utilizes artificial neural networks.
机译:对于能源市场而言,提前一天预测风力发电场的风力发电至关重要。但是,由于以下原因,风电功率预测的错误率很高:i)风电行为是随机的,非平稳的和间歇性的自然事实; ii)产生的风电功率与瞬时风速之间的关系是非线性的事实。在这项研究中,提出了一种在风电功率预测中利用EMoFS技术的新方法。为了验证所提方法的有效性,将所提方法的预测错误率与基于人工神经网络的方法所产生的预测错误率进行了比较。可以看出,与利用人工神经网络的通用方法相比,提出的方法产生了更好的结果。

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