"This work presents an appliance disaggregation technique to handle the fundamental goal of the Non-Intrusive Appliance Load Monitoring (NIALM) problem i.e., a simple breakdown of an appliance level energy consumption of a house. It also presents the modeling of individual appliances as load models using hidden Markov models and combined appliances as a single load model using factorial hidden Markov models. Granularity of the power readings of the disaggregated appliances matches with that of the readings collected at the service entrance. Accuracy of the proposed algorithm is evaluated using publicly released Tracebase data sets and UK-DALE data sets at various sampling intervals. The proposed algorithm achieved a success rate of 95% and above with Tracebase data sets at 5 second sampling resolution and 85% and above with UK-DALE data sets at 6 second sampling resolution"--Abstract, page iii.
McMillin, Bruce M.
Kimball, Jonathan W.
M.S. in Computer Science
Missouri University of Science and Technology
vii, 34 pages
© 2015 Anusha Sankara, All rights reserved.
Thesis - Open Access
Household appliances -- Energy consumption -- Computer simulation
Hidden Markov models
Energy consumption -- Measurement
Electronic OCLC #
Link to Catalog Record
Sankara, Anusha, "Energy disaggregation in NIALM using hidden Markov models" (2015). Masters Theses. 7414.