Text · dataset · 2017
Replication Data for Chen, V.L., Delmas, M.A., Locke S., Singh, A. 2017. Information Strategies for Energy Conservation: A Field Experiment in India. Energy Economics.
Listed in DataCite
Description
The data presented in this article are related to the research article entitled: “Information Strategies for Energy Conservation: A Field Experiment in India” (Victor L. Chen, Magali A. Delmas, Stephen L. Locke, Amarjeet Singh, 2017).The availability of high-resolution electricity data offers benefits to both utilities and consumers to understand the dynamics of energy consumption for example, between billing periods or times of peak demand.
However, few public datasets with high-temporal resolution have been available to researchers on electricity use, especially at the appliance-level. In this article, we describe data collected in a residential field experiment for 19 apartments at an Indian faculty housing complex during the period from August 1, 2013 to May 12, 2014. The dataset includes detailed information about electricity consumption.
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It also includes information on apartment characteristics and hourly weather variation to enable further studies of energy performance. These data can be used by researchers as training datasets to evaluate electricity usage consumption.
Links
Where it is published
- Repository landing page dataverse.harvard.edu/citation?persistentId=doi%3A10.7910%2FDVN%2F7MEXN4 ↗
landing page · from DataCite
- DOI doi.org/10.7910/dvn/7mexn4 ↗
DOI / persistent id · from DataCite
Documentation and papers
- Creative Commons Zero v1.0 Universal creativecommons.org/publicdomain/zero/1.0/legalcode ↗
license · from DataCite
- IsSupplementTo 10.1016/j.eneco.2017.09.004 doi.org/10.1016/j.eneco.2017.09.004 ↗
publication · from DataCite
Catalogue records · 2
- DataCite API api.datacite.org/dois/10.7910/dvn/7mexn4 ↗
metadata API · from DataCite
- DataCite Commons commons.datacite.org/doi.org/10.7910/dvn/7mexn4 ↗
catalogue entry · from DataCite
Topics
- Stated by source
- Economics and business
- From keywords
- Engineering · Social Science
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.7910/dvn/7mexn4 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · DataCite | connector:datacite@1.0.0 | /data/attributes/rightsList |
| concepts[field].fos:economics-and-business | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].local:field:engineering | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Engineering'] |
| concepts[field].local:field:social-science | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Social Sciences'] |
| created_date | source · DataCite | connector:datacite@1.0.0 | |
| description | source · DataCite | connector:datacite@1.0.0 | /data/attributes/descriptions |
| license | source · DataCite | connector:datacite@1.0.0 | /data/attributes/rightsList |
| publication_date | source · DataCite | connector:datacite@1.0.0 | /data/attributes/dates |
| spatial | source · DataCite | connector:datacite@1.0.0 | |
| title | source · DataCite | connector:datacite@1.0.0 | /data/attributes/titles/0/title |
| version_label | source · DataCite | connector:datacite@1.0.0 |