Compressive Sensing Based Power Signal Compression in Advanced Metering Infrastructure

被引：0
作者：
Lee, Yonggu [1 ]
Hwang, Euiseok [1 ]
Choi, Jinho [1 ]
机构：
[1] GIST, Gwangju, South Korea
来源：
2017 23RD ASIA-PACIFIC CONFERENCE ON COMMUNICATIONS (APCC): BRIDGING THE METROPOLITAN AND THE REMOTE | 2017年
关键词：
Advanced metering infrastructure; signal compression; compressive sensing; wavelet transform; ENERGY;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, we consider a compressive sensing (CS) based compression method for aggregated power signals of smart meters in advanced metering infrastructure (AMI). If detailed power signals with high sampling rates are available for energy management systems, advanced services such as demand response and power disaggregation can be provided. However, typical smart meters have limited bandwidth resources and may require aggressive data compression for supporting the intensively sampled data. In order to alleviate the overhead for the detailed power signal, a CS based compression scheme is proposed in this study to take advantage of the sparsity of power signals based on the appliance load superposition modeling. Through simulations, the CS based compression schemes demonstrate improved energy efficiency while maintaining good reconstruction performance, compared to the wavelet based compression.
引用
收藏
页码：93 / 98
页数：6
相关论文
共 23 条
[1]   DISCRETE COSINE TRANSFORM [J].
AHMED, N ;
NATARAJAN, T ;
RAO, KR .
IEEE TRANSACTIONS ON COMPUTERS, 1974, C 23 (01) :90-93
[2]   Empirical Characterization, Modeling, and Analysis of Smart Meter Data [J].
Barker, Sean ;
Kalra, Sandeep ;
Irwin, David ;
Shenoy, Prashant .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2014, 32 (07) :1312-1327
[3]  
Candès EJ, 2008, IEEE SIGNAL PROC MAG, V25, P21, DOI 10.1109/MSP.2007.914731
[4]  
Chiu SY, 2015, 2015 12TH ANNUAL IEEE INTERNATIONAL CONFERENCE ON SENSING, COMMUNICATION, AND NETWORKING (SECON), P453, DOI 10.1109/SAHCN.2015.7338346
[5]   A roofline model of energy [J].
Choi, Jee Whan ;
Bedard, Daniel ;
Fowler, Robert ;
Vuduc, Richard .
IEEE 27TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM (IPDPS 2013), 2013, :661-672
[6]   Energy and Quality Evaluation for Compressive Sensing of Fetal Electrocardiogram Signals [J].
Da Poian, Giulia ;
Brandalise, Denis ;
Bernardini, Riccardo ;
Rinaldo, Roberto .
SENSORS, 2017, 17 (01)
[7]  
Elafoudi G, 2014, 2014 6TH INTERNATIONAL SYMPOSIUM ON COMMUNICATIONS, CONTROL AND SIGNAL PROCESSING (ISCCSP), P36, DOI 10.1109/ISCCSP.2014.6877810
[8]   A hybrid compression method for integral images using discrete wavelet transform and discrete cosine transform [J].
Elharar, E. ;
Stern, Adrian ;
Hadar, Ofer ;
Javidi, Bahram .
JOURNAL OF DISPLAY TECHNOLOGY, 2007, 3 (03) :321-325
[9]   Disaggregated End-Use Energy Sensing for the Smart Grid [J].
Froehlich, Jon ;
Larson, Eric ;
Gupta, Sidhant ;
Cohn, Gabe ;
Reynolds, Matthew S. ;
Patel, Shwetak N. .
IEEE PERVASIVE COMPUTING, 2011, 10 (01) :28-39
[10]   Smart Grid Technologies: Communication Technologies and Standards [J].
Gungor, Vehbi C. ;
Sahin, Dilan ;
Kocak, Taskin ;
Ergut, Salih ;
Buccella, Concettina ;
Cecati, Carlo ;
Hancke, Gerhard P. .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2011, 7 (04) :529-539
123