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Publication details

Document type
Journal articles

Document subtype
Full paper

Title
An artificial neural network to assess the impact of neighbouring photovoltaic systems in power forecasting in Utrecht, the Netherlands

Participants in the publication
A.G.R. Vaz (Author)
B. Elsinga (Author)
W.G.J.H.M. van Sark (Author)
M.C. Brito (Author)
Dep. Engenharia Geográfica, Geofísica e Energia
 IDL
Date of Publication
2016-01-00

Where published
Renewable Energy

Publication Identifiers
ISSN - 0960-1481

Publisher
Elsevier BV

Volume
85

Starting page
631
Last page
641

Document Identifiers
DOI - https://doi.org/10.1016/j.renene.2015.06.061
URL - http://dx.doi.org/10.1016/j.renene.2015.06.061

Rankings
SCIMAGO Q1 (2016) - 1.661 - Renewable Energy, Sustainability and the Environment


Export

APA
A.G.R. Vaz, B. Elsinga, W.G.J.H.M. van Sark, M.C. Brito, (2016). An artificial neural network to assess the impact of neighbouring photovoltaic systems in power forecasting in Utrecht, the Netherlands. Renewable Energy, 85, 631-641. ISSN 0960-1481. eISSN . http://dx.doi.org/10.1016/j.renene.2015.06.061

IEEE
A.G.R. Vaz, B. Elsinga, W.G.J.H.M. van Sark, M.C. Brito, "An artificial neural network to assess the impact of neighbouring photovoltaic systems in power forecasting in Utrecht, the Netherlands" in Renewable Energy, vol. 85, pp. 631-641, 2016. 10.1016/j.renene.2015.06.061

BIBTEX
@article{39111, author = {A.G.R. Vaz and B. Elsinga and W.G.J.H.M. van Sark and M.C. Brito}, title = {An artificial neural network to assess the impact of neighbouring photovoltaic systems in power forecasting in Utrecht, the Netherlands}, journal = {Renewable Energy}, year = 2016, pages = {631-641}, volume = 85 }