Is disaggregation the holy grail of energy efficiency? The case of electricity

By K. Armel, Abhay Gupta, Gireesh Shrimali, Adrian Albert. 2013

641 citations recorded by the source corpus.

Subfields: Building and Construction, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/09b33c3ea1de5dcdd88bb1f4decec70041b1a6f2

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In Building and Construction

In Electrical and Electronic Engineering

In Renewable Energy, Sustainability and the Environment

Citations in the corpus

Smart Grids: A Cyber–Physical Systems Perspective (2016, background): “ber of critical tasks performed by human operators based on the raw data presented and past experiences [30].”
The ECO data set and the performance of non-intrusive load monitoring algorithms (2014, background): “In particular, feedback has shown to be effective when it is detailed and provided in a timely manner, it is tailored to individual households and it contains information on the consumption of individual appliances [2, 10, 12].”
Smart Electricity Meter Data Intelligence for Future Energy Systems: A Survey (2016, background): “As discussed in [22], another key factor could be the use of disaggregation techniques to extract underlying end use and appliance-level information from an aggregated energy signal.”
Revealing Household Characteristics from Smart Meter Data (2014, background): “This information allows in turn to provide detailed consumption feedback to the households [14, 15, 16].”
Tackling Climate Change with Machine Learning (2019, methodology): “[683] K Carrie Armel, Abhay Gupta, Gireesh Shrimali, and Adrian Albert.”
NILMTK: an open source toolkit for non-intrusive load monitoring (2014, background): “The field of non-intrusive load monitoring was founded 25 years ago when Hart proposed the first algorithm for the disaggregation of household energy usage [1, 12].”
Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey (2012, methodology): “The high end 117 NICs can read, write and report data up to 1 kHz, however changes are required in the meter 118 hardware to support sampling rate greater than 5 kHz [10].”