A Fuzzy C-means based User Clustering Method for Demand Response Regulation
作者单位：School of Automation Beijing Institute of Technology
会议名称：《第40届中国控制会议》
会议日期：2021年
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 080802[工学-电力系统及其自动化] 0808[工学-电气工程] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
关 键 词：Fuzzy C-means clustering Demand Response Curve Similarity Particle Swarm Optimization
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.