A smart forecasting approach to district energy management
- Submitting institution
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Cardiff University / Prifysgol Caerdydd
- Unit of assessment
- 12 - Engineering
- Output identifier
- 97127121
- Type
- D - Journal article
- DOI
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10.3390/en10081073
- Title of journal
- Energies
- Article number
- 1073
- First page
- -
- Volume
- 10
- Issue
- 8
- ISSN
- 1996-1073
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2017
- URL
-
https://doi.org/10.3390/en10081073
- Supplementary information
-
-
- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Accurate forecasting of distributed energy demand is essential to reduce resulting uncertainties from the increased penetration of variable renewable energy in the grid. This EU FP7 funded research developed a novel methodology to predict energy demand in individual homes and districts for smart energy management. The novelty lies in the discovery of the importance of prosumers’ socio-economic characteristics on improving prediction accuracy to 95.5%. The algorithm is further refined in H2020 DRIvE project (No. 774431) and in use by Enervalis in a neighbourhood in Woerden, Netherlands and by COMSA Corporacion in a commercial building in Barcelona, Spain.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -