Probabilistic Net Load Forecasting on London dataset 2019 (test)
2.97MAPERNN({1, 2, 24})
Evaluation Results
| Method | Links | ||||
|---|---|---|---|---|---|
| RNN({1, 2, 24})p={1, 2, 24}2022.09 | 2.97 | 125.18 | 33.64 | 6.17 | |
| Transformer2022.09 | 3.12 | 140.12 | 35.98 | 6.22 | |
| LSTM2022.09 | 3.13 | 138.6 | 36.14 | 6.24 | |
| RNN(1)p=12022.09 | 3.15 | 136.8 | 36.44 | 6.21 | |
| FNN2022.09 | 3.24 | 145.91 | 37.69 | 6.27 | |
| LightGBM2022.09 | 3.43 | 132.45 | 36.67 | 6.25 | |
| ARX2022.09 | 5.28 | 211.98 | 58.44 | 6.78 | |
| SARIMAX2022.09 | 5.56 | 218.48 | 66.01 | 6.96 | |
| Naïve2022.09 | 6.77 | 256.42 | 72.31 | 6.99 |