Real-time household energy prediction : approaches and applications for a blockchain-backed smart grid

In the current era of Internet of Things (IoT) devices, household solar panels, and increasingly aordable local energy storage, energy grid systems are facing a new set of challenges that they were not originally designed to support. Energy systems of the near future must be capable of supporting these new technologies, but new technology can also be leveraged to improve reliability and eciency overall. A major source of potential improvements comes from the increase of connected devices that are capable of dynamically adjusting their behavior, and offer new data that can be used for optimization and prediction. Energy predictions are used today at the bulk power system level to ensure demand is met through appropriate resource allocation. As energy systems become more responsive, prediction will be important at more granular system levels and timescales.

Name thesis:degree_name

Master

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

2019

Author dc:creator

• Lauer, Michelle(Michelle F.)

Advisor dc:contributor.advisor

• Marija Ilic.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

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

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/121676

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/121676