Day-Ahead Real-Time Pricing Strategy Based on the Price-Time-Type Elasticity of Demand

被引：0
|
作者：
Li, Zhongwen [1 ,2 ]
Huang, Haixin [1 ,3 ]
Zang, Chuanzhi [1 ]
Yu, Haibin [1 ]
机构：
[1] Chinese Acad Sci, Shenyang Inst Automat, Key Lab Networked Control Syst, Shenyang 110016, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Shenyang Ligong Univ, Informat Sci & Engn Coll, Shenyang 110159, Peoples R China
来源：
2013 15TH IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION TECHNOLOGY (ICCT) | 2013年
关键词：
demand response; real-time price; particle swarm optimization; electricity pricing strategy; demand side management;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The curtailment of the peak demand has great economic and environmental benefits. In this paper, an efficient price profile under the Real-Time Pricing (RTP) option is found out to optimize the regional domestic daily electric load curve. The domestic electric appliances are divided into eight categories, with respect to the difference of their self-price elasticity and cross-price elasticity. In order to set up a reasonable pricing strategy model, both the users' satisfaction and the price are taken into account. The program of RTP is taken and the Particle Swarm Optimization (PSO) algorithm is used to optimize the electricity price profile. Under the optimized price profile, the load curve tends to be more flat and the average price for the customer is lower than before, after the variation and shift of the electric power demand.
引用
收藏
页码：449 / 455
页数：7
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