Risk assessment method of power marketing operation based on convolutional neural network

Jingyi Liu, Jiawei Qi, Kun Wang, Zheng Liu
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Abstract

With the abolition of the sales price of China's industrial and commercial catalog, the competition in the power purchase market of industrial and commercial users is becoming increasingly stimulated. In order to solve the problem of difficult and low accuracy of power marketing operation risk assessment for industrial and commercial users, a power marketing operation risk assessment method based on convolutional neural network is proposed. Firstly, the neighbor propagation clustering method is used to analyze the clustering of industrial and commercial users, and the evaluation characteristics of industrial and commercial users are obtained. On this basis, the set of electric power marketing operation evaluation indicators is constructed. Secondly, the convolutional neural network is used to adjust the weight of the evaluation index, and the power marketing operation risk of industrial and commercial users is evaluated. Finally, the accuracy of the method was 96.37% when applied in a city. The application results show that the proposed method can effectively evaluate the risks of industrial and commercial power marketing.
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基于卷积神经网络的电力营销运营风险评估方法
随着中国工商目录销售价格的取消,工商用户购电市场的竞争日趋激烈。为了解决电力营销运营风险评估对工商用户难度大、准确率低的问题,提出了一种基于卷积神经网络的电力营销运营风险评估方法。首先,采用邻居传播聚类方法对工商业用户进行聚类分析,得到工商业用户的评价特征;在此基础上,构建了电力营销运营评价指标集。其次,利用卷积神经网络对评价指标的权重进行调整,对工商用户的电力营销运营风险进行评价;最后,该方法在某城市的应用准确率为96.37%。应用结果表明,该方法能有效地评估工业和商业电力营销的风险。
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