A Perspective on Reinforcement Learning in Price-based Demand Response for Smart Grid

被引：12

作者：

Lu, Renzhi ^{[1
]}

Hong, Seung Ho ^{[1
]}

Zhang, Xiongfeng ^{[1
]}

Ye, Xun ^{[1
]}

Song, Won Seok ^{[2
]}

机构：

[1] Hanyang Univ, Dept Elect Syst Engn, Ansan, South Korea

[2] Nestfield Co Ltd, Ansan 15588, South Korea

来源：

PROCEEDINGS 2017 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI) | 2017年

关键词：

Demand response; reinforcement learning; smart grid;

D O I：

10.1109/CSCI.2017.327

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a price-based demand response (DR) algorithm for energy management in a hierarchical electricity market. The pricing problem is formulated as a reinforcement learning (RL) model. Using RL, the service provider (SP) can adaptively decide the retail electricity price during the on-line learning process.

引用

页码：1822 / 1823

页数：2

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