Please use this identifier to cite or link to this item:
http://nopr.niscpr.res.in/handle/123456789/46940| Title: | Photovoltaic Power Generation Estimation Using Statistical Features and Artificial Neural Networks |
| Authors: | Elvira-Ortiz, D A Morinigo-Sotelo, D Romero-Troncoso, R J Osornio-Rios, R A |
| Keywords: | Artificial neural network;Photovoltaic systems;Statistical features;Power generation;Environmental factors |
| Issue Date: | Apr-2019 |
| Publisher: | NISCAIR-CSIR, India |
| Abstract: | Photovoltaic generation completely depends on environmental factors like sun irradiance and cell temperature. Therefore, it is necessary to develop methodologies that allow to predict the power generated by photovoltaic systems under different weather conditions. This work presents a methodology for estimating the power delivered by a photovoltaic inverter using statistical features coming from weather signals andan artificial neural network for predicting the power level delivered by the photovoltaic system. |
| Page(s): | 212-215 |
| ISSN: | 0975-1084 (Online); 0022-4456 (Print) |
| Appears in Collections: | JSIR Vol.78(04) [April 2019] |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| JSIR 78(4) 212-215.pdf | 616.21 kB | Adobe PDF | View/Open |
Items in NOPR are protected by copyright, with all rights reserved, unless otherwise indicated.