A data-driven approach for electricity load profile prediction of new supermarkets
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...
Autores principales: | Granell, R, Axon, C, Kolokotroni, M, Wallom, D |
---|---|
Formato: | Journal article |
Publicado: |
Elsevier
2019
|
Ejemplares similares
-
Using existing building stock to predict the electricity load profiles of new supermarkets
por: Granell, R, et al.
Publicado: (2018) -
Predicting electricity demand profiles of new supermarkets using machine learning
por: Granell, R, et al.
Publicado: (2020) -
A reduced-dimension feature extraction method to represent retail store electricity profiles
por: Granell, R, et al.
Publicado: (2022) -
Impacts of raw data temporal resolution using selected clustering methods on residential electricity load profiles
por: Granell, R, et al.
Publicado: (2015) -
Impacts of raw data temporal resolution using selected clustering methods on residential electricity load profiles
por: Granell, R, et al.
Publicado: (2014)