A Fuzzy C-means based User Clustering Method for Demand Response Regulation

被引：0
作者：
Li, Liang [1 ]
Wang, Liang [1 ]
Ma, Hongwei [1 ]
Han, Peidong [1 ]
Li, Ziyan [1 ]
Tian, Ye [1 ]
机构：
[1] Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China
来源：
2021 PROCEEDINGS OF THE 40TH CHINESE CONTROL CONFERENCE (CCC) | 2021年
关键词：
Fuzzy C-means clustering; Demand Response; Curve Similarity; Particle Swarm Optimization;
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 smart grid provides a good chance for the application of demand response technology, which could improve the renewable energy consumption and system stability. This paper proposes a Fuzzy C-means based User Clustering Method for Demand Response Regulation. Fuzzy C-means clustering method is adopted to find the user set which has the closest load characteristics with the renewable energy generation. This user set has the best probability to consume renewable energy. Then, particle swarm algorithm is used to adjust the electric price, which could slightly change the electric consumption behavior of the above user set. Finally, a higher renewable energy consumption rate could be achieved under a stable and economical condition.
引用
收藏
页码：5752 / 5757
页数：6
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