基于NARX神经网络的交直流电网自治能力评估方法

本发明提供了一种基于NARX神经网络的交直流电网自治能力评估方法,从源网荷储角度,提取训练交直流电网数据的分项评估指标;根据分项评估指标,确定原始评价矩阵及参考数列;使用熵值法,确定各分项评估指标的客观权重;根据原始评价矩阵、参考数列和客观权重,确定训练电网数据的综合灰关联度;根据分项评估指标和综合灰关联度,训练NARX神经网络的评估模型;基于训练的NARX神经网络的评估模型,评估交直流电网自治能力等级。本发明比传统方法选取的指标特征更具全局性,评估精度更高。 The invention provides an AC/DC power grid autonomous capability ev...

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Format Patent
LanguageChinese
Published 16.08.2022
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Summary:本发明提供了一种基于NARX神经网络的交直流电网自治能力评估方法,从源网荷储角度,提取训练交直流电网数据的分项评估指标;根据分项评估指标,确定原始评价矩阵及参考数列;使用熵值法,确定各分项评估指标的客观权重;根据原始评价矩阵、参考数列和客观权重,确定训练电网数据的综合灰关联度;根据分项评估指标和综合灰关联度,训练NARX神经网络的评估模型;基于训练的NARX神经网络的评估模型,评估交直流电网自治能力等级。本发明比传统方法选取的指标特征更具全局性,评估精度更高。 The invention provides an AC/DC power grid autonomous capability evaluation method based on an NARX neural network, and the method comprises the steps: extracting sub-item evaluation indexes of training AC/DC power grid data from the perspective of source grid load storage; determining an original evaluation matrix and a reference sequence according to the subitem evaluation indexes; determining an objective weight of each subitem evaluation index by using an entropy method; determining a comprehensive grey correlation degree of the training power grid data according to the original evaluationmatrix, the reference sequence and the objective weight; training an evaluation model of the NARX neural network according to the sub-item evaluation indexes and the comprehensive grey correl
Bibliography:Application Number: CN201910970200