Energy disaggregation via adaptive filtering

2013 51st Annual Allerton Conference on Communication, Control, and Computing, Allerton 2013

Volumn , Issue , 2013, Pages 173-180

  Dong, Roy ^a   Ratliff, Lillian J ^a   Ohlsson, Henrik ^a,b   Sastry, S Shankar ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b LINKÖPING UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE FILTERING; ELECTRIC POWER UTILIZATION;

DISAGGREGATION; OPTIMALITY;

ADAPTIVE FILTERS;

EID: 84897741671     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/Allerton.2013.6736521     Document Type: Conference Paper

References (25)

1. L. Perez-Lombard, J. Ortiz, and C. Pout, "A review on buildings energy consumption information," Energy and buildings, vol. 40, pp. 394-398, 2008
2. J. Creyts, A. Derkach, S. Nyquist, K. Ostrowski, and J. Stephenson, "Reducing U.S. greenhouse gas emissions: How much at what cost?" U.S. Greenhouse Gas Abatement Mapping Initiative, Tech. Rep., 2007
3. J. A. O . Laitner, K. Ehrhardt-Martinez, and V. McKinney, "Examining the scale of the behaviour energy efficiency continuum," in European Council for an Energy Efficient Economy, 2009
4. G. Crabtree, "Energy future report: 'energy future: think efficiency'," American Physical Society, Tech. Rep., 2008
5. K. C. Armel, A. Gupta, G. Shrimali, and A. Albert, "Is disaggregation the holy grail of energy efficiency? the case of electricity," Energy Policy, vol. 52, pp. 213-234, 2013 [Online]. Available:
6. K. Ehrhardt-Martinez, K. A. Donnelly, and J. A. Laitner, "Advanced metering initiatives and residential feedback programs: A meta-review for household electricity-saving opportunities," American Council for an Energy-Efficient Economy, Tech. Rep., June 2010
7. A. A. Cardenas, S. Amin, G. Schwartz, R. Dong, and S. Sastry, "A game theory model for electricity theft detection and privacy-aware control in ami systems," in 2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2012
8. R. Dong, L. Ratliff, H. Ohlsson, and S. S. Sastry, "A dynamical systems approach to energy disaggregation," arXiv, Apr. 2013
9. M. E. Berges, E. Goldman, H. S. Matthews, and L. Soibelman, "Enhancing electricity audits in residential buildings with nonintrusive load monitoring," Journal of Industrial Ecology, vol. 14, no. 5, pp. 844-858, 2010
10. M. Berges, E. Goldman, H. S. Matthews, and L. Soibelman, "Learning systems for electric consumption of buildings," in ASCI International Workshop on Computing in Civil Engineering, 2009
11. M. Zeifman and K. Roth, "Nonintrusive appliance load monitoring: Review and outlook," IEEE Transactions on Consumer Electronics,, vol. 57, no. 1, pp. 76-84, Feb. 2011
12. J. Z. Kolter and M. J. Johnson, "REDD: A public data set for energy disaggregation research," in Proceedings of the SustKDD Workshop on Data Mining Appliations in Sustainbility, 2011
13. J. Z. Kolter and A. Y. Ng, "Energy disaggregation via discriminative sparse coding," in Neural Information Processing Systems, 2010
14. S. Drenker and A. Kader, "Nonintrusive monitoring of electric loads," IEEE Computer Applications in Power,, vol. 12, no. 4, pp. 47-51, 1999
15. D. Rahayu, B. Narayanaswamy, S. Krishnaswamy, C. Labbe, and D. P. Seetharam, "Learning to be energy-wise: discriminative methods for load disaggregation," in Third International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet (e-Energy), 2012. IEEE, 2012, pp. 1-4
16. 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 and Buildings, vol. 30, no. 3, pp. 245-259, 1999
17. H. Kim, M. Marwah, M. F. Arlitt, G. Lyon, and J. Han, "Unsupervised disaggregation of low frequency power measurements," in SDM'11, 2011, pp. 747-758
18. J. Z. Kolter and T. Jaakkola, "Approximate inference in additive factorial HMMs with application to energy disaggregation," in Proceedings of the International Conference on Artificial Intelligence and Statistics, 2012
19. M. J. Johnson and A. S. Willsky, "Bayesian Nonparametric Hidden Semi-Markov Models," Massachusetts Institute of Technology, Tech. Rep. arXiv:1203.1365, 2012
20. O. Parson, S. Ghosh, M. Weal, and A. Rogers, "Nonintrusive load monitoring using prior models of general appliance types," in 26th AAAI Conference on Artificial Intelligence, 2012
21. S. Pattem, "Unsupervised disaggregation for non-intrusive load monitoring," in 11th International Conference on Machine Learning and Applications (ICMLA), 2012, vol. 2. IEEE, 2012, pp. 515-520
22. H. Shao, M. Marwah, and N. Ramakrishnan, "A temporal motif mining approach to unsupervised energy disaggregation," in Proceedings of 1st International Non-Intrusive Load Monitoring Workshop, 2012
23. H. Ohlsson, L. Ratliff, R. Dong, and S. S. Sastry, "Blind identification of ARX models with piecewise constant inputs," arXiv, Mar. 2013
24. L. Ljung, System Identification-Theory for the User. Prentice Hall, 1999
25. F. Gustafsson, Adaptive Filtering and Change Detection. John Wiley & Sons, Ltd, 2000.