Photovoltaic power analysis and prediction using machine learning methods
| dc.contributor.author | Shehada, Halah | |
| dc.date.accessioned | 2021-07-29T16:04:34Z | |
| dc.date.available | 2021-07-29T16:04:34Z | |
| dc.date.graduationmonth | August | en_US |
| dc.date.published | 2021 | en_US |
| dc.description.abstract | The stochastic nature of Photovoltaic power directly affects the stability of the grid. PV power forecasting allows power stations to know beforehand how much PV power will be available, which ensures that the grid remains in stabilized condition. PV power from India is analyzed and predicted using machine learning methods | en_US |
| dc.description.advisor | Mohammad Bagher Shadmand | en_US |
| dc.description.degree | Master of Science | en_US |
| dc.description.department | Department of Electrical and Computer Engineering | en_US |
| dc.description.level | Masters | en_US |
| dc.identifier.uri | https://hdl.handle.net/2097/41580 | |
| dc.language.iso | en_US | en_US |
| dc.subject | Photovoltaic | en_US |
| dc.subject | Random Forest | en_US |
| dc.subject | Confusion Matrix | en_US |
| dc.title | Photovoltaic power analysis and prediction using machine learning methods | en_US |
| dc.type | Report | en_US |
