中国电力 ›› 2020, Vol. 53 ›› Issue (2): 9-19.doi: 10.11930/j.issn.1004-9649.201803194

• 技术经济 • 上一篇    下一篇

基于电力客户评估的差异化电价套餐研究

喻小宝1, 谭忠富2, 屈高强3   

  1. 1. 上海电力大学 经济与管理学院, 上海 200090;
    2. 华北电力大学 经济与管理学院, 北京 102006;
    3. 国网宁夏电力有限公司, 宁夏 银川 750001
  • 收稿日期:2018-03-30 修回日期:2019-06-20 出版日期:2020-02-05 发布日期:2020-02-05
  • 作者简介:喻小宝(1989-),男,博士,讲师,从事电力市场研究,E-mail:yuxiaobao1222@163.com;谭忠富(1964-),男,博士生导师,从事电力市场、能源经济研究,E-mail:tanzhongfubeijing@126.com
  • 基金资助:
    国家自然科学基金资助项目(我国减少清洁能源发电弃能的机制设计及其模拟模型研究,71573084);上海市哲学社会科学规划课题(电力市场环境下交易模式评估及市场主体信用度评估体系研究,2018EGL005)。

Research on Differentiated Price Package Based on Power Customer Evaluation

YU Xiaobao1, TAN Zhongfu2, QU Gaoqiang3   

  1. 1. School of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China;
    2. School of Economics and Management, North China Electric Power University, Beijing 102206, China;
    3. State Grid Ningxia Electric Power Co. Ltd., Yinchuan 750001, China
  • Received:2018-03-30 Revised:2019-06-20 Online:2020-02-05 Published:2020-02-05
  • Supported by:
    This work is supported by National Natural Science Foundation of China (Research on Mechanism Design and Simulation Model of Reducing Waste Energy Generation and Energy Dissipation in China, No.71573084) and Shanghai Municipal Social Science Foundation (Research on Trading Mode Evaluation and Market Subject Credit Evaluation System in Electricity Market Environment, No.2018EGL005).

摘要: 随着售电侧改革的推进,售电市场逐步扩大,售电公司在研究如何降低电力批发市场购电成本的同时,应当加强对电力零售市场用户的研究。构建电力客户评估指标体系,引入多目标优化的权重设计模型,基于电力客户评估结果对用户进行类别划分,并设计了相对应的差异化套餐。算例结果表明:在各类指标权重结果里,收益类指标中的年用电量权重结果最高;用户被划分到3个区间,评估结果高低与用户类别划分是基本匹配的。

关键词: 电力市场, 价差套餐, 售电公司, 差异化, 客户评估

Abstract: With the advancement of the demand side reform, the electricity market is gradually expanding. While studying how to reduce the purchase cost in the wholesale market, the electricity retailers should pay attention to the research of the electricity users in the retail market. The paper built a power customer evaluation index system by introducing a weight design model of multi-objective optimization, and classified electricity users based on the assessment results, and designed a corresponding differential package. A case study shows that among the weights of various indicators, the weight of the electricity consumption in the revenue index is the highest. The electricity users are divided into three categories, and the evaluation results are matched with the users classification.

Key words: electricity market, spread package, electricity retailer, differentiation, customer evaluation