Research Article
Data-Driven Photovoltaic System Modeling Based on Nonlinear System Identification
Table 2
Best fit with different input and output nonlinearity.
| Hammerstein-Wiener model | Input nonlinearity | Output nonlinearity | Final predicted error (FPE) | Loss function | Best fit (%) |
| Piecewise linear | Piecewise linear | 6.723 | 6.723 | 80.25 | Piecewise linear | Sigmoid network | 5.036 | 5.036 | 86.11 | Piecewise linear | Saturation | 1.751 | 1.751 | 92.83 | Piecewise linear | Dead zone | 1.023 | 1.023 | 92.24 | Piecewise linear | Wavelet network | 2.083 | 2.082 | 88.11 | Sigmoid network | Piecewise linear | 1.265 | 1.265 | 77.94 | Sigmoid network | Sigmoid network | 3.547 | 3.547 | 81.05 | Sigmoid network | Saturation | 2.016 | 2.016 | 89.45 | Sigmoid network | Dead zone | 4.952 | 4.951 | 85.37 | Sigmoid network | Wavelet network | 0.1694 | 0.1693 | 63.09 | Saturation | Piecewise linear | 1.262 | 1.262 | 92.22 | Saturation | Sigmoid network | 1.199 | 1.199 | 92.44 | Saturation | Saturation | FE | FE | FE | Saturation | Dead zone | FE | FE | FE | Saturation | Wavelet network | 0.7606 | 0.7601 | 85.83 | Dead zone | Piecewise linear | 0.3974 | 0.3974 | 93.4 | Dead zone | Sigmoid network | 1.464 | 1.464 | 93.98 | Dead zone | Saturation | FE | FE | FE | Dead zone | Dead zone | FE | FE | FE | Dead zone | Wavelet network | 0.2972 | 0.2972 | 90.86 | Wavelet network | Piecewise linear | 1.717 | 1.716 | 91.42 | Wavelet network | Sigmoid network | 2.038 | 2.037 | 89.61 | Wavelet network | Saturation | 131.5 | 131.5 | ā0.7279 | Wavelet network | Dead zone | 2.054 | 2.054 | 90.09 | Wavelet network | Wavelet network | 0.3643 | 0.364 | 93.81 |
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FE: failed estimation.
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