Residential Load Pattern Analysis for Smart Grid Applications Based on Audio Feature EEUPC

Yunzhi Wang, Xiangdong Wang, Yueliang Qian, Haiyong Luo, Fujiang Ge, Yuhang Yang and Yingju Xia
Additional contact information
Yunzhi Wang: Institute of Computing Technology, Chinese Academy of Sciences and Graduate University of Chinese Academy of Sciences, China
Xiangdong Wang: Institute of Computing Technology, Chinese Academy of Sciences, China
Yueliang Qian: Institute of Computing Technology, Chinese Academy of Sciences, China
Haiyong Luo: Institute of Computing Technology, Chinese Academy of Sciences, China
Fujiang Ge: Fujitsu Research & Development Center Co., Ltd., China
Yuhang Yang: Fujitsu Research & Development Center Co., Ltd., China
Yingju Xia: Fujitsu Research & Development Center Co., Ltd., China

International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC), 2011, vol. 3, issue 2, 39-53

Abstract: The smart grid is an important application field of the Internet of things. This paper presents a method of user electricity consumption pattern analysis for smart grid applications based on the audio feature EEUPC. A novel similarity function based on EEUPC is adapted to support clustering analysis of residential load patterns. The EEUPC similarity exploits features of peaks and valleys on curves instead of directly comparing values and obtains better performance for clustering analysis. Moreover, the proposed approach performs load pattern clustering, extracts a typical pattern for each cluster, and gives suggestions toward better power consumption for each typical pattern. Experimental results demonstrate that the EEUPC similarity is more consistent with human judgment than the Euclidean distance and higher clustering performance can be achieved for residential electric load data.

Date: 2011
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/japuc.2011040106 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:japuc0:v:3:y:2011:i:2:p:39-53

Access Statistics for this article

International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC) is currently edited by Tao Gao

More articles in International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC) from IGI Global
Bibliographic data for series maintained by Journal Editor ().