Comprehensive energy efficiency rating evaluation model of enterprise power based on grid big data

2021 International Conference on Information Control, Electrical Engineering and Rail Transit (ICEERT) Pub Date : 2021-10-01 DOI:10.1109/iceert53919.2021.00025

Wenrui Yan, Fanmao Jiang, Aihua Liu, J. Xu, S. Zhang

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引用次数: 2

Abstract

In the enterprise power comprehensive energy efficiency rating evaluation model, there is a problem of unclear definition of user attributes, which affects the evaluation accuracy. The enterprise power comprehensive energy efficiency rating evaluation model is designed based on power grid big data. Preprocess massive big data information, screen out effective and complete user data, establish user portrait based on power grid big data, and clarify user attribute labels. The comprehensive energy efficiency evaluation index system of enterprise power is designed according to the user portrait. Based on the evaluation of each bottom index, it is scored by the normal distribution method. Calculate the weight of the same level elements, construct the power comprehensive energy efficiency grade evaluation model, and use the clustering algorithm to realize the grade evaluation. The results show that the average accuracy of the model is 95.23%, which is 12.79% and 8.53% higher than the results of the enterprise power comprehensive energy efficiency grade evaluation model based on decision tree and random forest. Therefore, this model can effectively determine the comprehensive energy efficiency level of enterprises.

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基于电网大数据的企业电力综合能效等级评价模型

在企业电力综合能效等级评价模型中，存在用户属性定义不清的问题，影响了评价的准确性。设计了基于电网大数据的企业电力综合能效等级评价模型。对海量大数据信息进行预处理，筛选出有效完整的用户数据，基于电网大数据建立用户画像，明确用户属性标签。根据用户画像设计了企业电力综合能效评价指标体系。根据对各底层指标的评价，采用正态分布法进行评分。计算同级要素的权重，构建电力综合能效等级评价模型，并利用聚类算法实现等级评价。结果表明，该模型的平均准确率为95.23%，比基于决策树和随机森林的企业电力综合能效等级评价模型的结果分别高出12.79%和8.53%。因此，该模型可以有效地确定企业的综合能效水平。

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来源期刊

2021 International Conference on Information Control, Electrical Engineering and Rail Transit (ICEERT)

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