Name
Abstract | ||
|---|---|---|
In this work, we aim at perform short-term prediction on the solar irradiance in order to allow the Photovoltaics (PV) operators to manage and allocate energy supplies. Making accurate short-term prediction helps ensure the stability of power supply without the need to reserve too much energy. All-sky cameras are devices that can be used to monitor the behaviors of the sun and the clouds. By analyzing all-sky images, we extract features that can be used to predict solar irradiance via a trained regression model. The results of this work could provide very useful information for PV operators to ensure greater efficiency of the solar energy supply. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2632856.2632909 | ICIMCS |
Keywords | Field | DocType |
algorithms,miscellaneous,all-sky image,regression,solar irradiance prediction | Computer vision,Regression analysis,Simulation,Computer science,Image processing,Solar energy,Photovoltaics,Real-time computing,Sky,Operator (computer programming),Artificial intelligence,Solar irradiance | Conference |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hsu-Yung Cheng | 1 | 243 | 23.56 |
| Chih-Chang Yu | 2 | 32 | 8.93 |