Household User Behavior Analysis based on Power Data
文献类型：会议论文
| 作者 | Li, Xin2 ; Zang CZ(臧传治)1,4; Qin, Xiaoning3
|
| 出版日期 | 2019 |
| 会议日期 | June 3-5, 2019 |
| 会议地点 | Nanchang, China |
| 关键词 | User Behavior Clustering Strategy Smart Grids |
| 页码 | 5814-5818 |
| 英文摘要 | With the popularization of smart grid application and the rapid development of big data technology, a large amount of user power consumption data is recorded and stored, making user power consumption behavior analysis the key content of demand side management. The user behavior state is identified by the variation of power amplitude of power load based on hidden Markov model. Users are mapped to potential feature space by means of price elasticity information regularization matrix decomposition. Further, K-means clustering algorithm is adopted to segment users. The strategy can improve the rationality of user power consumption behavior clustering, more effectively grasp the form of user power consumption load, reduce the peak load of power and balance power supply and demand, which is of great significance to the demand side management of smart grid. |
| 源文献作者 | Institute of Electrical and Electronics Engineers Inc. |
| 产权排序 | 2 |
| 会议录 | Proceedings of the 31st Chinese Control and Decision Conference, CCDC 2019
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-7281-0105-7 |
| WOS记录号 | WOS:000555859006012 |
| 源URL | [http://ir.sia.cn/handle/173321/25810]  |
| 专题 | 沈阳自动化研究所_工业控制网络与系统研究室 |
| 通讯作者 | Zang CZ(臧传治) |
| 作者单位 | 1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2.School of Information Engineering, Shenyang University, Shenyang 110044, China 3.Shenyang Dongling Power Supply Branch Company, Shenyang, Shenyang 110043, China 4.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China |
| 推荐引用方式 GB/T 7714 | Li, Xin,Zang CZ,Qin, Xiaoning. Household User Behavior Analysis based on Power Data[C]. 见:. Nanchang, China. June 3-5, 2019. |
入库方式： OAI收割
来源：沈阳自动化研究所
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