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 5
The forecasting results and optimized parameters of the proposed hybrid model EEMD-GA-FAC/SAC in site 2.
| | | | | Time | Actual value (m/s) | Forecasting value (m/s) | MAPE (%) | MSE (m2/s2) | MAE (m/s) |
| Observation
site 2 | EEMD-GA-FAC | 0.0425 | 0:00 | 7.3 | 6.99 | 4.31 | 0.0992 | 0.3149 | | 0.9957 | 2:00 | 8.5 | 8.30 | 2.34 | 0.0395 | 0.1988 | | 0.2433 | 4:00 | 8.1 | 8.10 | 0.00 | 0.0000 | 0.0001 | | 0.0372 | 6:00 | 8 | 8.23 | 2.89 | 0.0536 | 0.2315 | | 0.0187 | 8:00 | 7.2 | 7.20 | 0.02 | 0.0000 | 0.0013 | | 0.1959 | 10:00 | 7 | 7.00 | 0.00 | 0.0000 | 0.0001 | | 0.2481 | 12:00 | 8.4 | 7.90 | 5.89 | 0.2450 | 0.4950 | | 0.0000 | 14:00 | 11.6 | 11.42 | 1.59 | 0.0342 | 0.1849 | | 0.0000 | 16:00 | 8.9 | 9.57 | 7.48 | 0.4428 | 0.6654 | | 1.0000 | 18:00 | 10.9 | 10.40 | 4.62 | 0.2541 | 0.5041 | | 0.8061 | 20:00 | 10.6 | 10.92 | 3.06 | 0.1052 | 0.3243 | | 0.0000 | 22:00 | 11.4 | 11.45 | 0.45 | 0.0026 | 0.0508 | | EEMD-GA-SAC | 0.6201 | 0:00 | 7.3 | 6.72 | 7.98 | 0.3394 | 0.5826 | | 1.0000 | 2:00 | 8.5 | 8.39 | 1.28 | 0.0118 | 0.1086 | | 0.2561 | 4:00 | 8.1 | 8.10 | 0.00 | 0.0000 | 0.0000 | | 0.0379 | 6:00 | 8 | 8.19 | 2.35 | 0.0354 | 0.1882 | | 0.3939 | 8:00 | 7.2 | 6.63 | 7.98 | 0.3301 | 0.5746 | | 0.0209 | 10:00 | 7 | 6.58 | 6.04 | 0.1786 | 0.4226 | | 0.0149 | 12:00 | 8.4 | 7.05 | 16.12 | 1.8333 | 1.3540 | | 0.0210 | 14:00 | 11.6 | 10.59 | 8.70 | 1.0177 | 1.0088 | | 0.9990 | 16:00 | 8.9 | 9.47 | 6.45 | 0.3300 | 0.5745 | | 1.0000 | 18:00 | 10.9 | 11.05 | 1.42 | 0.0240 | 0.1548 | | 1.0000 | 20:00 | 10.6 | 10.96 | 3.41 | 0.1306 | 0.3614 | | 0.0000 | 22:00 | 11.4 | 11.39 | 0.06 | 0.0001 | 0.0073 |
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