Is disaggregation the holy grail of energy efficiency? The case of electricity
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Household energy disaggregation breaks down overall electricity consumption into energy use by individual appliances, which can help facilitate behavior change.
“Household energy disaggregation breaks down overall electricity consumption into energy use by individual appliances (see also Section 4.1) [33], which can help facilitate behavior change [772].”
From Tackling climate change with machine learning (2023) · cites this paper as [33]
A variety of ML techniques have been used to effectively disaggregate household energy, such as spectral clustering, Hidden Markov Models, and neural networks.
“A variety of ML techniques have been used to effectively disaggregate household energy, such as spectral clustering, Hidden Markov Models, and neural networks [33].”
From Tackling climate change with machine learning (2023) · cites this paper as [33]
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- Authors
- Carrie Armel, K., Gupta, A., Shrimali, G., & Albert, A.
- Affiliations
- Indian School of Business (IN)
- Stanford University (US)
- Venue
- Energy Policy
- Publisher
- Elsevier BV
- Published
- 2013-01
- Volume
- 52
- Pages
- 213-234
- ISSN
- 0301-4215 (ISSN-L)
- OpenAlex
- W2043279449
- Cited by
- 595
- References
- 78
- Citations by year
- 2026: 15 · 2025: 29 · 2024: 24 · 2023: 44 · 2022: 45 · 2021: 49 · 2020: 68 · 2019: 60 · 2018: 57 · 2017: 57 · 2016: 48 · 2015: 43 · 2014: 48 · 2013: 7 · 2012: 1
- FWCI
- 20.25
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Energy Policy (publishedVersion)
- Digital Eprints Services at ISB (DESI) (Indian School of Business) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Department of Energy ARPA-E (DE-AR0000018)
- California Energy Commission (PIR-10-054)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Energy, Environment, and Transportation Policies
- Keywords
- non-intrusive load monitoring, smart meters, residential energy efficiency, energy conservation, cost-effectiveness, building energy monitoring
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