A projection neural network for optimal demand response in smart grid environment

被引：0
|
作者：
Yao Yao
Xing He
Tingwen Huang
Chaojie Li
Dawen Xia
机构：
[1] Southwest University,Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering
[2] Texas A&M University at Qatar,Department of Mathematics
[3] RMIT University,School of Electrical and Computer Engineering
[4] Guizhou Minzu University,School of Information Engineering
来源：
Neural Computing and Applications | 2018年 / 29卷
关键词：
Demand response; Projection neural network; Satisfaction function;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper presents a smart grid model that fully considers the power consumption types of users and the features of electricity price. A satisfaction function is added into the bill function to balance the user experience of electricity usage and the consumption of load. For the purpose of minimizing the electricity bill of all users, a single-layer projection neural network (PNN) is used, which is proven to be global convergence. And the simulation results reveal that the effectiveness and peculiarities of the proposed PNN.
引用
收藏
页码：259 / 267
页数：8
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