Name
Abstract | ||
|---|---|---|
Prediction with uncertainty quantification (UQ) is becoming a vital part of the grid management with the increased uncertainty caused by the recent installation of renewable power sources. Specialized algorithms are developed and applied to predict electricity demand, renewable generations and other non-fossil-fuel generations in point predictions. The required fossil fuel generation (RFFG) of a g... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/IJCNN52387.2021.9533704 | 2021 International Joint Conference on Neural Networks (IJCNN) |
Keywords | DocType | ISSN |
Renewable energy sources,Uncertainty,Upper bound,Artificial neural networks,Maintenance engineering,Wind power generation,Cost function | Conference | 2161-4393 |
ISBN | Citations | PageRank |
978-1-6654-3900-8 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| H M Dipu Kabir | 1 | 4 | 1.39 |
| Abbas Khorsavi | 2 | 0 | 0.34 |
| Md Shihanur Rahman | 3 | 0 | 0.34 |
| Mohammad Anwar Hosen | 4 | 8 | 3.84 |
| Saeid Nahavandi | 5 | 1545 | 219.71 |