Interpreting human activity from electrical consumption data through non-intrusive load monitoring

Non-intrusive load monitoring (NILM) has three distinct advantages over today's smart meters. First, it offers accountability. Few people know where their kWh's are going. Second, it is a maintenance tool. Signs of wear are detectable through their electrical signal. Third, it provides awareness of human activity within a network. Each device has an electrical fingerprint, and specific devices imply associated human actions. From voltage and current measurements at a single point on the network, non-intrusive load monitoring (NILM) disaggregates appliance-level information. This information is available remotely in bandwidth-constrained environments. Four real-world field tests at military micro grids and commercial buildings demonstrate the utility of the NILM in reducing electrical demand, enabling condition-based maintenance, and inferring human activity from electrical activity.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2014

Author dc:creator

• Gillman, Mark Daniel

Advisor dc:contributor.advisor

• Steven B. Leeb and John S. Donnal.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/90136

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/90136