@inproceedings{81f2b67c9ce34615a33651197659433f,
title = "A Fuzzy C-means based User Clustering Method for Demand Response Regulation",
abstract = "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.",
keywords = "Curve Similarity, Demand Response, Fuzzy C-means clustering, Particle Swarm Optimization",
author = "Liang Li and Liang Wang and Hongwei Ma and Peidong Han and Ziyan Li and Ye Tian",
note = "Publisher Copyright: {\textcopyright} 2021 Technical Committee on Control Theory, Chinese Association of Automation.; 40th Chinese Control Conference, CCC 2021 ; Conference date: 26-07-2021 Through 28-07-2021",
year = "2021",
month = jul,
day = "26",
doi = "10.23919/CCC52363.2021.9549450",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "5752--5757",
editor = "Chen Peng and Jian Sun",
booktitle = "Proceedings of the 40th Chinese Control Conference, CCC 2021",
address = "United States",
}
