Short-term PV power forecasting using hybrid GASVM technique
Download
Download
Download![[thumbnail of Short-term-PV-power-forecasting-using-hybrid-GASVM-techn_2019_Renewable-Ener.pdf]](https://vuir.vu.edu.au/style/images/fileicons/text.png)
Short-term-PV-power-forecasting-using-hybrid-GASVM-techn_2019_Renewable-Ener.pdf
- Accepted Version
(2MB)
Restricted to Repository staff only
Available under license: Creative Commons Attribution Non-commercial No Derivatives
Export
VanDeventer, William, Jamei, Elmira 
ORCID: 0000-0002-4270-0326, Thirunavukkarasu, Gokul Sidarth ORCID: 0000-0002-5126-5979, Seyedmahmoudian, Mehdi, Soon, TK, Horan, Ben ORCID: 0000-0002-6723-259X, Mekhilef, Saad ORCID: 0000-0001-8544-8995 and Stojcevski, Alex
(2019)
Short-term PV power forecasting using hybrid GASVM technique.
Renewable Energy, 140.
pp. 367-379.
ISSN 0960-1481
Dimensions Badge
Altmetric Badge
| Item type | Article |
| URI | https://vuir.vu.edu.au/id/eprint/38309 |
| DOI | 10.1016/j.renene.2019.02.087 |
| Official URL | https://www.sciencedirect.com/science/article/pii/... |
| Subjects | Historical > FOR Classification > 0906 Electrical and Electronic Engineering Current > Division/Research > College of Science and Engineering |
| Keywords | solar energy; support vector machines; genetic algorithm; photovoltaic systems; PV solar forecasting; PV power; renewable energy; Geelong; weather patterns |
| Citations in Scopus | 154 - View on Scopus |
| Download/View statistics | View download statistics for this item |
CORE (COnnecting REpositories)