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Stratification-Based Wind Power Forecasting in a High-Penetration Wind Power System Using a Hybrid Model

机译:基于混合模型的高渗透率风电系统中基于分层的风电预测

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摘要

This paper proposes a novel stratification-based wind power forecasting method and develops a hybrid forecasting model at different stratifications using charged system search algorithm. The proposed model applies the concept of segmentation from the theory of optimal stratification to forecast short-term wind power outputs. Additionally, the proposed method elucidates different weighting values of each individual model at different segmentation blocks. Based on the forecasting results, the proposed stratification-based hybrid model outperforms traditional stand-alone models and unstratified hybrid models in terms of forecasting accuracy, which verifies the proposed forecasting model for accurate wind power forecasting.
机译:本文提出了一种新的基于分层的风电功率预测方法,并利用收费系统搜索算法建立了不同分层的混合预测模型。所提出的模型将最佳分层理论中的分段概念应用于预测短期风电输出。另外,所提出的方法阐明了在不同的分割块处每个个体模型的不同的加权值。基于预测结果,提出的基于分层的混合模型在预测精度方面优于传统的独立模型和非分层的混合模型,验证了所提出的预测模型对风电功率的准确预测。

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