Name
Title | ||
|---|---|---|
Spatiotemporal Behind-the-Meter Load and PV Power Forecasting via Deep Graph Dictionary Learning |
Abstract | ||
|---|---|---|
In recent years, with the rapid growth of rooftop photovoltaic (PV) generation in distribution networks, power system operators call for accurate forecasts of the behind-the-meter (BTM) load and PV generation. However, the existing forecasting methodologies are incapable of quantifying such BTM measurements as the smart meters can merely measure the net load time series. Motivated by this challeng... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TNNLS.2020.3042434 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | DocType | Volume |
Spatiotemporal phenomena,Load modeling,Forecasting,Feature extraction,Time series analysis,Predictive models,Hidden Markov models | Journal | 32 |
Issue | ISSN | Citations |
10 | 2162-237X | 1 |
PageRank | References | Authors |
0.37 | 17 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mahdi Khodayar | 1 | 1 | 0.70 |
| Guangyi Liu | 2 | 223 | 36.37 |
| Jun Wang | 3 | 626 | 84.82 |
| M. Okyay Kaynak | 4 | 2378 | 178.15 |
| Mohammad E. Khodayar | 5 | 66 | 10.53 |