Particle-swarm-optimization-based nonintrusive demand monitoring and load identification in smart meters

IEEE Transactions on Industry Applications

Volumn 49, Issue 5, 2013, Pages 2229-2236

  Chang, Hsueh Hsien ^a   Lin, Lung Shu ^b   Chen, Nanming ^c   Lee, Wei Jen ^d  

^a JINWEN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

^b CHUNG SHAN INSTITUTE OF SCIENCE AND TECHNOLOGY   (Taiwan)

^c NATIONAL TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

^d UNIVERSITY OF TEXAS AT ARLINGTON   (United States)

Author keywords

Artificial neural networks (ANNs); nonintrusive load monitoring (NILM); particle swarm optimization (PSO); smart meters

Indexed keywords

ELECTROMAGNETIC TRANSIENTS PROGRAM SIMULATIONS; LOAD IDENTIFICATION; LOAD MONITORING SYSTEMS; MEASUREMENT SYSTEM; MULTIPLE OPERATIONS; NONINTRUSIVE LOAD MONITORING; RECOGNITION ACCURACY; TRAINING ALGORITHMS;

ALGORITHMS; COMPUTATIONAL EFFICIENCY; MEASUREMENTS; NEURAL NETWORKS; PARTICLE SWARM OPTIMIZATION (PSO); SMART METERS;

ELECTRIC LOAD MANAGEMENT;

EID: 84884566151     PISSN: 00939994     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIA.2013.2258875     Document Type: Article

References (22)

1. BP Statistical Review of World Energy, BP Global, Houston, TX, USA, Jun. 2010
2. Bureau of Energy, Long-Term Demand Forecast and Energy Report, Ministry of Econom. Affairs, Taipei, Taiwan, Jan. 2011
3. G. W. Hart, "Nonintrusive appliance load monitoring," Proc. IEEE, vol. 80, no. 12, pp. 1870-1891, Dec. 1992
4. S. B. Leeb, "A conjoint pattern recognition approach to nonintrusive load monitoring," Ph.D. dissertation, Dept. Elect. Eng. Comput. Sci., Massachusetts Inst. Technol., Cambridge, MA, USA, 1993
5. A. I. Cole and A. Albicki, "Nonintrusive identification of electrical loads in a three-phase environment based on harmonic content," in Proc. IEEE Instrum. Meas. Technol. Conf., 2000, pp. 24-29
6. A. I. Cole and A. Albicki, "Data extraction for effective non-intrusive identification of residential power loads," in Proc. IEEE Instrum. Meas. Technol. Conf., 1998, pp. 812-815
7. A. I. Cole and A. Albicki, "Algorithm for non-intrusive identification of residential appliances," in Proc. IEEE Int. Symp. Circuits Syst., 1998, pp. 338-341
8. H. H. Chang, K. L. Chen, Y. P. Tsai, and W. J. Lee, "A new measurement method for power signatures of non-intrusive demand monitoring and load identification," IEEE Trans. Ind. Appl., vol. 48, no. 2, pp. 764-771, Mar./Apr. 2012
9. L. K. Norford and S. B. Leeb, "Non-intrusive electrical load monitoring in commercial buildings based on steady-state and transient load-detection algorithms," Energy Build., vol. 24, no. 1, pp. 51-64, Jan. 1996 (Pubitemid 126339890)
10. S. R. Shaw and C. R. Laughman, "A Kalman-filter spectral envelope preprocessor," IEEE Trans. Instrum. Meas., vol. 56, no. 5, pp. 2010-2017, Oct. 2007 (Pubitemid 47455931)
11. S. R. Shaw, S. B. Leeb, L. K. Norford, and R. W. Cox, "Nonintrusive load monitoring and diagnostics in power systems," IEEE Trans. Instrum. Meas., vol. 57, no. 7, pp. 1445-1454, Jul. 2008
12. M. L. Marceau and R. Zmeureanu, "Nonintrusive load disaggregation computer program to estimate the energy consumption of major end users in residential buildings," Energy Convers. Manage., vol. 41, no. 13, pp. 1389-1403, Sep. 2000
13. L. Farinaccio and R. Zmeureanu, "Using a pattern recognition approach to disaggregate the total electricity consumption in a house into the major end-uses," Energy Build., vol. 30, no. 3, pp. 245-259, Aug. 1999 (Pubitemid 30509852)
14. M. Baranski and J. Voss, "Genetic algorithm for pattern detection in NIALM systems," in Proc. IEEE Syst., Man Cybern., Conf., 2004, pp. 3462-3468 (Pubitemid 40408370)
15. D. Srinivasan,W. S. Ng, and A. C. Liew, "Neural-network-based signature recognition for harmonic source identification," IEEE Trans. Power Del., vol. 21, no. 1, pp. 398-405, Jan. 2006 (Pubitemid 43279826)
16. C. N. Hsu, H. J. Huang, and D. Schuschel, "The ANNIGMA-wrapper approach to fast feature selection for neural nets," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 32, no. 2, pp. 207-212, Apr. 2002 (Pubitemid 34249379)
17. N. Kwak and C. H. Choi, "Input feature selection for classification problems," IEEE Trans. Neural Netw., vol. 13, no. 1, pp. 143-159, Jan. 2002 (Pubitemid 34236844)
18. M. Kudo and J. Sklansky, "Comparison of algorithms that select features for pattern classifiers," Pattern Recognit., vol. 33, no. 1, pp. 25-41, Jan. 2000. (Pubitemid 32081876)
19. L. Liu, S. Yang, and D. Wang, "Particle swarm optimization with composite particles in dynamic environments," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 40, no. 6, pp. 1634-1648, Dec. 2010
20. B. I. Kazem and N. F. H. Zangana, "A neural network based real time controller for turning process," Jordan J. Mech. Ind. Eng., vol. 1, no. 1, pp. 43-55, Sep. 2007
21. J. Kennedy and R. Eberhart, "Particle swarm optimization," in Proc. IEEE Int. Conf. Neural Netw. IV, 1995, pp. 1942-1948
22. Y. Y. Hong and B. Y. Chen, "Locating switched capacitor using wavelet transform and hybrid principal component analysis network," IEEE Trans. Power Del., vol. 22, no. 2, pp. 1145-1152, Apr. 2007.