A new hourly dataset for photovoltaic energy production for the continental USA.

Distributed computing Ensemble simulation Renewable energy Solar photovoltaic

Journal

Data in brief
ISSN: 2352-3409
Titre abrégé: Data Brief
Pays: Netherlands
ID NLM: 101654995

Informations de publication

Date de publication:
Feb 2022
Historique:
received: 17 09 2021
revised: 07 01 2022
accepted: 10 01 2022
entrez: 10 2 2022
pubmed: 11 2 2022
medline: 11 2 2022
Statut: epublish

Résumé

This new dataset is an ensemble of solar photovoltaic energy production simulations over the continental US. The simulations are carried out in three steps. First, a weather forecast system is used for the predictions of incoming insolation; then, forecast ensembles with 21 members are generated using the Analog Ensemble technique; finally, each ensemble member is used to simulate 13 different solar panels. In total, there are

Identifiants

pubmed: 35141367
doi: 10.1016/j.dib.2022.107824
pii: S2352-3409(22)00036-1
pmc: PMC8813589
doi:

Types de publication

Journal Article

Langues

eng

Pagination

107824

Informations de copyright

© 2022 The Author(s).

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships which have, or could be perceived to have, influenced the work reported in this article.

Auteurs

Weiming Hu (W)

Scripps Institution of Oceanography, University of California, San Diego, United States.
Institute for Computational and Data Sciences, The Pennsylvania State University, United States.

Guido Cervone (G)

Institute for Computational and Data Sciences, The Pennsylvania State University, United States.
Earth and Environmental Systems Institute, The Pennsylvania State University, United States.
Research Application Laboratory, National Center for Atmospheric Research, United States.

Andre Merzky (A)

Department of Electrical and Computer Engineering, Rutgers University, United States.

Matteo Turilli (M)

Department of Electrical and Computer Engineering, Rutgers University, United States.

Shantenu Jha (S)

Department of Electrical and Computer Engineering, Rutgers University, United States.

Classifications MeSH