Research Article
The Importance of Distance between Photovoltaic Power Stations for Clear Accuracy of Short-Term Photovoltaic Power Forecasting
Table 6
Summary of accuracy assessment of NARX neural network forecasting model for each location.
| | Metrics/Locations | Rabat 60kWp | Rabat 2kWp | Casablanca 3kWp |
| | RMSENARX 27 (%) | 10.145 | — | 11.178 | | RMSEPERSISTENCE 27 (%) | 23.339 | — | 22.887 | | (%) | 0.565 | — | 0.511 | | MAE NARX 27 (%) | 5.130 | — | 8.333 | | MAEPERSISTENCE 27 (%) | 15.642 | — | 15.448 | | (%) | 0.672 | — | 0.460 | | RMSENARX 28 (%) | 5.948 | — | 6.570 | | RMSEPERSISTENCE 28 (%) | 15.570 | | 15.098 | | (%) | 0.617 | — | 0.564 | | MAE NARX 28 (%) | 3.508 | — | 3.593 | | MAEPERSISTENCE 28 (%) | 9.297 | — | 9.041 | | (%) | 0.622 | — | 0.602 | | RMSENARX 29 (%) | 8.036 | — | 11.178 | | RMSEPERSISTENCE 29 (%) | 16.261 | — | 15.763 | | (%) | — | — | — | | MAE NARX 29 (%) | 4.841 | — | 7.082 | | MAEPERSISTENCE 29 (%) | 9.210 | — | 8.977 | | (%) | 0.474 | — | 0.211 | | RMSENARX 25 (%) | — | 10.043 | — | | RMSEPERSISTENCE 25 (%) | — | 75.119 | — | | (%) | — | 0.866 | — | | MAE NARX 25 (%) | — | 5.491 | — | | MAEPERSISTENCE 25 (%) | — | 79.015 | — | | (%) | — | 0.930 | — | | RMSENARX 26 (%) | — | 12.099 | — | | RMSEPERSISTENCE 26 (%) | — | 17.641 | — | | (%) | — | 0.314 | — | | MAE NARX 26 (%) | — | 7.699 | — | | MAEPERSISTENCE 26 (%) | — | 11.412 | — | | (%) | — | 0.325 | — | | RMSENARX 27 (%) | — | 8.945 | — | | RMSEPERSISTENCE 27 (%) | | 11.212 | — | | (%) | — | 0.202 | — | | MAE NARX 27 (%) | — | 6.393 | — | | MAEPERSISTENCE 27 (%) | — | 6.688 | — | | (%) | — | 0.044 | — |
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