Journal article
A data-driven approach for electricity load profile prediction of new supermarkets
- Abstract:
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Predicting the electricity demand of new supermarkets will help with design, planning, and future energy management. Instead of creating complex site-specific thermal engineering models, simplified statistical energy prediction models as we propose can be useful to energy managers. We have designed and implemented a data-driven method to predict the ’electricity daily load profile’ (EDLP) for new stores. Our preliminary work exploits a data-set of hourly electricity meter readings for 196 UK ...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Version of record, pdf, 782.8KB)
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- Publisher copy:
- 10.1016/j.egypro.2019.02.087
Authors
Funding
+ Engineering and Physical Sciences Research Council
More from this funder
Funding agency for:
Granell, R
Wallom, D
Grant:
EP/R511742/1
EP/R511742/1
Bibliographic Details
- Publisher:
- Elsevier Publisher's website
- Journal:
- Energy Procedia Journal website
- Volume:
- 161
- Pages:
- 242-250
- Publication date:
- 2019-03-18
- Acceptance date:
- 2018-08-15
- DOI:
- EISSN:
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1876-6102
- ISSN:
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1876-6102
Item Description
- Keywords:
- Pubs id:
-
pubs:935870
- UUID:
-
uuid:3abdb19c-b475-446a-b1d3-d72148f744b7
- Local pid:
- pubs:935870
- Source identifiers:
-
935870
- Deposit date:
- 2018-10-31
Terms of use
- Copyright holder:
- Granell et al
- Copyright date:
- 2019
- Notes:
- © 2019 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.
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