Research Article
Research and Application of a New Hybrid Forecasting Model Based on Genetic Algorithm Optimization: A Case Study of Shandong Wind Farm in China
Table 6
The forecasting results and optimized parameters of the proposed hybrid model EEMD-GA-FAC/SAC in site 3.
| | | | | Time | Actual value (m/s) | Forecasting value (m/s) | MAPE (%) | MSE (m2/s2) | MAE (m/s) |
| Observation
site 3 | EEMD-GA-FAC | 0.9996 | 0:00 | 8.3 | 8.87 | 6.88 | 0.3257 | 0.5707 | | 1.0000 | 2:00 | 9.4 | 9.10 | 3.18 | 0.0893 | 0.2988 | | 0.0413 | 4:00 | 9.2 | 9.20 | 0.00 | 0.0000 | 0.0000 | | 1.0000 | 6:00 | 8.1 | 8.14 | 0.52 | 0.0018 | 0.0424 | | 0.1189 | 8:00 | 8.3 | 8.30 | 0.00 | 0.0000 | 0.0000 | | 0.1095 | 10:00 | 7.1 | 7.64 | 7.65 | 0.2950 | 0.5431 | | 0.2280 | 12:00 | 8.8 | 8.80 | 0.00 | 0.0000 | 0.0000 | | 0.0553 | 14:00 | 10.3 | 10.30 | 0.00 | 0.0000 | 0.0004 | | 0.0914 | 16:00 | 10.1 | 10.56 | 4.57 | 0.2130 | 0.4615 | | 0.0000 | 18:00 | 12.2 | 11.48 | 5.92 | 0.5221 | 0.7226 | | 0.9465 | 20:00 | 12.2 | 11.98 | 1.77 | 0.0467 | 0.2162 | | 0.2387 | 22:00 | 11 | 11.00 | 0.00 | 0.0000 | 0.0002 | | EEMD-GA-SAC | 0.9994 | 0:00 | 8.3 | 8.70 | 4.79 | 0.1578 | 0.3973 | | 0.9927 | 2:00 | 9.4 | 9.26 | 1.51 | 0.0201 | 0.1419 | | 0.1626 | 4:00 | 9.2 | 9.20 | 0.00 | 0.0000 | 0.0000 | | 0.9876 | 6:00 | 8.1 | 8.14 | 0.52 | 0.0018 | 0.0424 | | 0.0290 | 8:00 | 8.3 | 8.30 | 0.00 | 0.0000 | 0.0000 | | 0.1180 | 10:00 | 7.1 | 7.64 | 7.56 | 0.2882 | 0.5368 | | 0.2376 | 12:00 | 8.8 | 8.80 | 0.00 | 0.0000 | 0.0000 | | 0.0523 | 14:00 | 10.3 | 10.30 | 0.00 | 0.0000 | 0.0002 | | 0.0928 | 16:00 | 10.1 | 10.54 | 4.33 | 0.1910 | 0.4370 | | 0.9992 | 18:00 | 12.2 | 11.58 | 5.06 | 0.3809 | 0.6171 | | 0.9465 | 20:00 | 12.2 | 11.98 | 1.77 | 0.0467 | 0.2162 | | 0.0536 | 22:00 | 11 | 11.00 | 0.01 | 0.0000 | 0.0008 |
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