文章摘要
曹昉,李欣宁,刘思佳,等.基于消费者参考价格决策及用户粘性的售电套餐优化[J].电力系统自动化. DOI: 10.7500/AEPS20171128011.
caofang,lixinning,, et al.Optimization of Sales Package for End-users Considering Customer Stickiness Based on Consumer’s reference pricing Decision[J].Automation of Electric Power Systems. DOI: 10.7500/AEPS20171128011.
基于消费者参考价格决策及用户粘性的售电套餐优化
Optimization of Sales Package for End-users Considering Customer Stickiness Based on Consumer’s reference pricing Decision
DOI:10.7500/AEPS20171128011
关键词: 电价零售套餐  用户粘性  同化系数  IRP模型  决策矩阵
KeyWords: electricity price retail package  user stickiness  assimilation coefficient  IRP model  user
上网日期:2018-06-11
基金项目:
作者单位E-mail
曹昉 华北电力大学 电气与电子工程学院 caofang@ncepu.edu.cn 
李欣宁 华北电力大学 电气与电子工程学院 lixinning5965@163.com 
刘思佳 国网能源研究院 liusijia@sgeri.sgcc.com.cn 
李赛 华北电力大学 电气与电子工程学院 electricianli@foxmail.com 
摘要:
      在未来的电力零售市场,更多的售电企业为规避风险,提高市场占有率和持续性,有必要向拥有零售选择权的终端用户提供科学合理并具有竞争力的售电套餐,论文提出一种售电套餐设计优化的新思路。首先,考虑用户消费的偏好行为,引入分类同化系数建立消费者IRP决策模型,定义单个用户的粘性行为(或称为惰性行为),建立单个用户粘性函数。然后,论文建立用户决策矩阵反应群体用户对套餐的选择情况,建立基于用户粘性和决策矩阵的售电企业总效用目标函数,以固定费用和单位费用结合的套餐结构为基础,以套餐价格为变量,对最优目标进行搜索。接着,论文采用交叉粒子群算法,将传统的搜索方式改进为以元胞数组为单位的种群多区域的同时搜索。同时,利用对决策矩阵的两次修正模拟用户无偏好条件下的绝对理性消费和存在偏好条件下的非理性消费。最后进行算例分析,通过对比优化前后潜在用户对套餐的选择情况,验证了模型的可行性与优化效果。#$NL关键词:电价零售套餐;用户粘性;同化系数;IRP模型;决策矩阵
Abstract:
      In the future electricity retail market, it is necessary for more power-selling enterprises considering avoiding risks and improving the company"s market share and sustainability by providing end-users with scientific and reasonable and competitive electricity sales package in order to protect the end-users who have the retail options. A new idea for sales package design optimization is proposed in this paper. First of all, the consumer’s IRP decision model considering the consumer"s preference behavior and introducing classification assimilation coefficient is built in this paper, and defines the sticky behavior (or inertia behavior) of a single user, and establishes a single user"s sticky function. Then, this paper establishes the user choice matrix of response group users and the total utility function of sales utility based on user"s stickiness and decision matrix. Considering package price based on the package structure of fixed costs and unit costs combined with as the variable, search for the best goal. Then, the improved cross-particle swarm optimization is selected to improve the traditional search method to search multiple populations simultaneously in the unit of the cell array. At the same time, two amendments has been made to the decision matrix to simulate the irrational consumption under the condition of no preference and the preference of existence. Finally, a case study is conducted to verify the feasibility and optimization effect of the model by comparing the potential customers" choices of packages before and after optimization..#$NLKeywords: electricity price retail package; user stickiness; assimilation coefficient; IRP model; user"s choice matrix;
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