Artificial Intelligence Based Methodology for Load Disaggregation at Bulk Supply Point
- Submitting institution
-
The University of Manchester
- Unit of assessment
- 12 - Engineering
- Output identifier
- 51337993
- Type
- D - Journal article
- DOI
-
10.1109/tpwrs.2014.2337872
- Title of journal
- IEEE Transactions on Power Systems
- Article number
- -
- First page
- 795
- Volume
- 30
- Issue
- 2
- ISSN
- 0885-8950
- Open access status
- Out of scope for open access requirements
- Month of publication
- July
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
-
F - EEE
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work led to the development of a demand forecasting tool demonstrated in Portuguese distribution network within EU project SUSTAINABLE (https://www.iit.comillas.edu/proyectos/mostrar_proyecto.php.en?nombre_abreviado=SUSTAINABLE_FP7) and the award of EU projects NOBEL GRID ( https://nobelgrid.eu/consortium/), CROSSBOW (http://crossbowproject.eu/) and several conference keynote lectures.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
