| 魏小曼,余昆,陈星莺,颜拥,张爽,景伟强.基于 Affinity propagation和 K-means算法的电力大用户细分方法分析[J].电力需求侧管理,2018,20(1):15-19 |
| 基于 Affinity propagation和 K-means算法的电力大用户细分方法分析 |
| Analysis of power large user segmentation based on Affinity propagationand K.means algorithm |
| 投稿时间：2017-08-23 修订日期：2017-09-25 |
| DOI：10.3969/j.issn.1009-1831.2018.01.005 |
| 中文关键词: 大用户细分 细分指标 聚类算法 用户特征群 |
| 英文关键词: large user segmentation segmentation index clustering algorithm user characteristic group |
| 基金项目: |
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| 中文摘要: |
| 力大用户是供电企业的重点用户，其在电力市场环境下的潜在价值以及发展趋势与供电企业的利益密切相关。为了识别出有价值的大用户行为与价值特征，提出基于近邻传播( Affinity propagation, AP)和 K.means算法相结合的电力大用户细分方法。首先，从现有指标中提取出关键细分指标，并考虑电力大用户近期和长期的电费增长率，提出评估大用户发展潜力的细分指标；其次，将 AP和 K.means 2种算法相结合，基于细分指标对电力大用户进行细分，以解决寻找初始聚类中心以及聚类数的问题，同时避免 K.means聚类时容易陷入局部最优的问题；算例分析以浙江某地区的用户数据为基础进行算例分析，验证所提出的电力大用户细分方法切实可行。 |
| 英文摘要: |
| Power large users are the key users of power sup.ply enterprises and their potential value and development trend inpower market environment are closely related to the profit of powersupply enterprises.In order to identify valuable user behavior andvalue characteristics, a large user segmentation method based on APand K.means algorithm is proposed.First of all, from the existing in.dicators to extract the key sub.indicators, and consider the recentlarge and long.term power consumption rate of electricity, put for.ward to assess the development potential of large users of the break.down of indicators.Secondly, the AP and K.means are combined tosegment the large power users to solve the problem of finding the ini.tial clustering center and the number of clusters.At the same time, itis easy to avoid the local optimization when K.means clustering prob.lem; finally, based on the user data of a region in Zhejiang province,the author analyzes the feasibility of the proposed method. |
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