GreenThrift: Optimizing Carbon and Cost for Flexible Residential Loads Article Swipe
Phuthipong Bovornkeeratiroj
,
Walid A. Hanafy
,
David Irwin
,
Prashant Shenoy
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1145/3724408
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1145/3724408
Reducing buildings’ carbon emissions is an important sustainability challenge. While scheduling flexible building loads has been previously used for a variety of grid and energy optimizations, carbon footprint reduction using such flexible loads poses new challenges since such methods need to balance both energy and carbon costs while also reducing user inconvenience from delaying such loads. This article highlights the potential conflict between electricity prices and carbon emissions and the resulting tradeoffs in carbon-aware and cost-aware load scheduling. To address this tradeoff, we propose GreenThrift, a home automation system that leverages the scheduling capabilities of smart appliances and knowledge of future carbon intensity and cost to reduce both the carbon emissions and costs of flexible energy loads. At the heart of GreenThrift is an optimization technique that automatically computes schedules based on user configurations and preferences. We evaluate the effectiveness of GreenThrift using real-world carbon intensity data, electricity prices, and load traces from multiple locations and across different scenarios and objectives. Our results show that GreenThrift can replicate the offline optimal and retains 97% of the savings when optimizing the carbon emissions. Moreover, we show how GreenThrift can balance the conflict between carbon and cost and retain 95.3% and 85.5% of the potential carbon and cost savings, respectively.
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- Landing Page
- https://doi.org/10.1145/3724408
- OA Status
- green
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4408831916
All OpenAlex metadata
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https://openalex.org/W4408831916Canonical identifier for this work in OpenAlex
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https://doi.org/10.1145/3724408Digital Object Identifier
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GreenThrift: Optimizing Carbon and Cost for Flexible Residential LoadsWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-03-25Full publication date if available
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Phuthipong Bovornkeeratiroj, Walid A. Hanafy, David Irwin, Prashant ShenoyList of authors in order
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https://doi.org/10.1145/3724408Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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Carbon fibers, Computer science, Environmental science, Algorithm, Composite numberTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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27Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.emissions | 3, 67, 110 |
| abstract_inverted_index.footprint | 27 |
| abstract_inverted_index.important | 6 |
| abstract_inverted_index.intensity | 102, 145 |
| abstract_inverted_index.knowledge | 98 |
| abstract_inverted_index.leverages | 90 |
| abstract_inverted_index.locations | 154 |
| abstract_inverted_index.potential | 60, 202 |
| abstract_inverted_index.reduction | 28 |
| abstract_inverted_index.replicate | 167 |
| abstract_inverted_index.resulting | 70 |
| abstract_inverted_index.scenarios | 158 |
| abstract_inverted_index.schedules | 129 |
| abstract_inverted_index.technique | 125 |
| abstract_inverted_index.tradeoff, | 81 |
| abstract_inverted_index.tradeoffs | 71 |
| abstract_inverted_index.appliances | 96 |
| abstract_inverted_index.automation | 87 |
| abstract_inverted_index.challenge. | 8 |
| abstract_inverted_index.challenges | 35 |
| abstract_inverted_index.cost-aware | 75 |
| abstract_inverted_index.emissions. | 181 |
| abstract_inverted_index.highlights | 58 |
| abstract_inverted_index.optimizing | 178 |
| abstract_inverted_index.previously | 16 |
| abstract_inverted_index.real-world | 143 |
| abstract_inverted_index.scheduling | 10, 92 |
| abstract_inverted_index.GreenThrift | 121, 141, 165, 186 |
| abstract_inverted_index.electricity | 63, 147 |
| abstract_inverted_index.objectives. | 160 |
| abstract_inverted_index.scheduling. | 77 |
| abstract_inverted_index.GreenThrift, | 84 |
| abstract_inverted_index.buildings’ | 1 |
| abstract_inverted_index.capabilities | 93 |
| abstract_inverted_index.carbon-aware | 73 |
| abstract_inverted_index.optimization | 124 |
| abstract_inverted_index.preferences. | 135 |
| abstract_inverted_index.automatically | 127 |
| abstract_inverted_index.effectiveness | 139 |
| abstract_inverted_index.inconvenience | 51 |
| abstract_inverted_index.respectively. | 207 |
| abstract_inverted_index.configurations | 133 |
| abstract_inverted_index.optimizations, | 25 |
| abstract_inverted_index.sustainability | 7 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.09371787 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |