A neural network based computational model to predict the output power of different types of photovoltaic cells.
In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experime...
Saved in:
| Main Authors: | WenBo Xiao, Gina Nazario, HuaMing Wu, HuaMing Zhang, Feng Cheng |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2017-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0184561&type=printable |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Improved Mathematical Model for Computing Power Output of Solar Photovoltaic Modules
by: Abdul Qayoom Jakhrani, et al.
Published: (2014-01-01) -
Output Power Prediction of a Photovoltaic Module Through Artificial Neural Network
by: Muhammad Aseer Khan, et al.
Published: (2022-01-01) -
Interval Forecast of Photovoltaic Power Output Based on GAN
by: GU Yong-tao, et al.
Published: (2021-04-01) -
Active Power Allocation Method for Photovoltaic Cluster Considering Output and Electricity Price Uncertainty
by: Hua LI, et al.
Published: (2023-08-01) -
Photovoltaic Power Output Prediction using Graphical User Interface and Artificial Neural Network
by: Cempaka Amalin Mahadzir, et al.
Published: (2023-12-01)