Recommendation Method for Electricity Retail Plan Based on Bi-level Affinity Propagation Clustering and Multigranular Hesitant Fuzzy Sets

MA Yuanqian; LI Qiyuan; CHEN Hanzhong; ZHANG Zhi; LIN Zhenzhi; YANG Li

doi:10.7500/AEPS20220110005

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Recommendation Method for Electricity Retail Plan Based on Bi-level Affinity Propagation Clustering and Multigranular Hesitant Fuzzy Sets

Basic Research | 更新时间：2025-06-16

- Recommendation Method for Electricity Retail Plan Based on Bi-level Affinity Propagation Clustering and Multigranular Hesitant Fuzzy Sets
- Automation of Electric Power Systems Vol. 47, Issue 1, Pages: 96-104(2023)
- 作者机构：
  
  1.浙江理工大学机械与自动控制学院，浙江省杭州市 310018
  2.浙江大学电气工程学院，浙江省杭州市 310058
- 作者简介：
- 基金信息：
  
  Zhejiang Provincial Natural Science Foundation of China(LQ22E070009)
- DOI：10.7500/AEPS20220110005
  CLC：
- Received：10 January 2022，
  
  Revised：2022-03-22，
  
  Published Online：12 July 2022，
  
  Published：10 January 2023
- 稿件说明：
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马愿谦,李启源,陈汉忠等.基于BLAP聚类和多粒度犹豫模糊集的售电套餐推荐方法[J].电力系统自动化,2023,47(1):96-104.

MA Yuanqian,LI Qiyuan,CHEN Hanzhong,et al.Recommendation Method for Electricity Retail Plan Based on Bi-level Affinity Propagation Clustering and Multigranular Hesitant Fuzzy Sets[J].Automation of Electric Power Systems,2023,47(1):96-104.
马愿谦,李启源,陈汉忠等.基于BLAP聚类和多粒度犹豫模糊集的售电套餐推荐方法[J].电力系统自动化,2023,47(1):96-104. DOI： 10.7500/AEPS20220110005.

MA Yuanqian,LI Qiyuan,CHEN Hanzhong,et al.Recommendation Method for Electricity Retail Plan Based on Bi-level Affinity Propagation Clustering and Multigranular Hesitant Fuzzy Sets[J].Automation of Electric Power Systems,2023,47(1):96-104. DOI： 10.7500/AEPS20220110005.

摘要

现有基于用户评价信息的售电套餐推荐方法因忽略了差异化用户评价信息的多样性，且仅考虑了用户擅长评价售电套餐所有属性的情形，给推荐结果带来较大偏差。为此，提出了一种基于双层邻近传播(BLAP)聚类和多粒度犹豫模糊语言评价集的售电套餐推荐方法。首先，提出了基于用户画像标签体系和BLAP聚类的样本用户集划分方法，以辨别用电特性相似的用户；然后，考虑多粒度犹豫模糊语言评价集和权重不完整信息，提出了样本用户集对售电套餐选择的模糊评价方法；接着，提出了基于样本用户集评价信息的新用户满意度评估方法和售电套餐的全排序推荐方法，以实现售电公司对售电套餐的精准推荐。最后，以中国某地区用户为对象进行算例分析，结果表明基于BLAP聚类和多粒度犹豫模糊集的售电套餐推荐方法能够帮助售电公司提高推荐质量，进而提升用户满意度，增强用户黏性。

Abstract

The existing recommendation methods for the electricity retail plans based on the evaluation information of customers ignore the diversity of differentiated customer evaluation information and only consider the cases

in which customers are good at evaluating all the attributes of the electricity sales

which will bring great deviation to the recommendation results. To this end

a recommendation method for the electricity retail plans based on the bi-level affinity propagation (BLAP) clustering algorithm and multigranular hesitant fuzzy linguistic evaluation set is proposed. Firstly

the division method for the sample customer set based on the customer portrait label system and BLAP clustering algorithm is proposed to identify the customers with similar electricity consumption characteristics. Secondly

considering the multigranular hesitant fuzzy linguistic evaluation set and incomplete weight information

a fuzzy evaluation method for the selection of electricity retail plan by the sample customer set is put forward. Thirdly

based on the information of the sample customer set

the new evaluation method of new customers and the full-ranking recommendation method for the electricity retail plan are proposed

which can realize the accurate recommendation of electricity retail plans by electricity retail companies. Finally

taking customers in an area of China as a case for study

the results show that the electricity retail plan recommendation method for electricity retail plans based on BLAP clustering and multigranular hesitant fuzzy set can help electricity retail companies improve the recommendation quality. Thus

the satisfaction of customers is improved

and the stickiness of customers is enhanced.

关键词

Keywords

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