Harmonic Distortion Prediction Model of a Grid-Tie Photovoltaic Inverter Using an Artificial Neural Network
Abstract
:1. Introduction
2. Materials and Methods
2.1. Description of the Site
2.2. Measurement Procedure
3. Analysis of the Measured Data
3.1. Meteorological Data
3.2. Power Quality Measurement Analysis
4. Current Harmonics Forecasting with ANN
4.1. ANN Model Evaluation
4.2. Simulations, Results, and Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Manufacturer | Kaco |
---|---|
Model | Powador 12.0 TL3 |
Circuit design | 6-pulse transformerless IGBT 1 |
DC side | |
Parameter | Value |
Maximum PV generator input power (kW) | 12 |
Maximum power point voltage range (V) | 280–800 |
Starting voltage (V) | 250 |
Maximum open-circuit voltage (V) | 1000 |
Number of string inputs | 2 |
Maximum short-circuit current (A) | 22.4 |
AC side | |
Rated power (kW) | 10 |
Rated current (A) | 14.5 |
Grid voltage (V) | 400/230 |
Distortion factor (THDI) (%) | 2.22 |
Maximum efficiency (%) | 98 |
European efficiency (%) | 97.5 |
Parameter | Solar Irradiance | Ambient Temperature |
---|---|---|
Mean value | 175.17 W/m2 | 14.65 °C |
Minimum value | 7.26 W/m2 | −11.21 °C |
Maximum value | 1172.03 W/m2 | 37.16 °C |
Standard deviation | 248.91 W/m2 | 9.76 °C |
Coefficient of variation | 1.42 | 0.67 |
Parameter | 5th Current Harmonic (A) | 7th Current Harmonic (A) | 11th Current Harmonic (A) | 13th Current Harmonic (A) |
---|---|---|---|---|
Mean value | 0.0147 | 0.0142 | 0.0137 | 0.0130 |
Maximum value | 0.8489 | 0.4733 | 0.4310 | 0.2915 |
Minimum value | 0.1354 | 0.0961 | 0.0752 | 0.0437 |
Standard deviation | 0.1278 | 0.0911 | 0.0662 | 0.0402 |
Coefficient of variation | 1.0596 | 1.0550 | 1.1374 | 1.0869 |
Model Name | Input Parameters | Architecture |
---|---|---|
MLPNN 1 | G | 1-11-4 |
MLPNN 2 | G, Tamb | 2-11-4 |
MLPNN 3 | G, Tamb, t | 3-11-4 |
MLPNN 4 | G | 1-11-5-4 |
MLPNN 5 | G, Tamb | 2-11-5-4 |
MLPNN 6 | G, Tamb, t | 3-11-5-4 |
Model Version | Current Harmonic | Validation | |||
---|---|---|---|---|---|
R | d | RMSE (A) | MAE (A) | ||
MLPNN 1 (1-11-4) | 5th | 0.9356 | 0.9555 | 0.0693 | 0.0455 |
7th | 0.971 | 0.9804 | 0.032 | 0.0221 | |
11th | 0.9437 | 0.9598 | 0.0376 | 0.0252 | |
13th | 0.8459 | 0.8426 | 0.0374 | 0.021 | |
MLPNN 2 (1-11-5-4) | 5th | 0.9358 | 0.9563 | 0.0687 | 0.0454 |
7th | 0.9706 | 0.9798 | 0.0323 | 0.022 | |
11th | 0.9437 | 0.9599 | 0.0375 | 0.0245 | |
13th | 0.8534 | 0.8567 | 0.0363 | 0.0216 |
Model Version | Current Harmonic | Validation | |||
---|---|---|---|---|---|
R | d | RMSE (A) | MAE (A) | ||
MLPNN 3 (1-11-4) | 5th | 0.9381 | 0.9662 | 0.0658 | 0.0438 |
7th | 0.9676 | 0.9804 | 0.0324 | 0.0224 | |
11th | 0.9465 | 0.972 | 0.0336 | 0.0217 | |
13th | 0.8712 | 0.9124 | 0.0309 | 0.0185 | |
MLPNN 4 (1-11-5-4) | 5th | 0.9354 | 0.9647 | 0.0673 | 0.0436 |
7th | 0.9626 | 0.9771 | 0.0343 | 0.0222 | |
11th | 0.945 | 0.9702 | 0.0345 | 0.0235 | |
13th | 0.8743 | 0.9225 | 0.03 | 0.0193 |
Model Version | Current Harmonic | Validation | |||
---|---|---|---|---|---|
R | d | RMSE (A) | MAE (A) | ||
MLPNN 5 (1-11-4) | 5th | 0.9376 | 0.9664 | 0.066 | 0.045 |
7th | 0.9634 | 0.9801 | 0.033 | 0.0222 | |
11th | 0.9429 | 0.9694 | 0.0362 | 0.024 | |
13th | 0.8678 | 0.926 | 0.0299 | 0.0183 | |
MLPNN 6 (1-11-5-4) | 5th | 0.9369 | 0.9666 | 0.0651 | 0.0428 |
7th | 0.9686 | 0.9834 | 0.0306 | 0.0201 | |
11th | 0.9469 | 0.9722 | 0.034 | 0.0229 | |
13th | 0.8801 | 0.9253 | 0.0293 | 0.0191 |
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Žnidarec, M.; Klaić, Z.; Šljivac, D.; Dumnić, B. Harmonic Distortion Prediction Model of a Grid-Tie Photovoltaic Inverter Using an Artificial Neural Network. Energies 2019, 12, 790. https://doi.org/10.3390/en12050790
Žnidarec M, Klaić Z, Šljivac D, Dumnić B. Harmonic Distortion Prediction Model of a Grid-Tie Photovoltaic Inverter Using an Artificial Neural Network. Energies. 2019; 12(5):790. https://doi.org/10.3390/en12050790
Chicago/Turabian StyleŽnidarec, Matej, Zvonimir Klaić, Damir Šljivac, and Boris Dumnić. 2019. "Harmonic Distortion Prediction Model of a Grid-Tie Photovoltaic Inverter Using an Artificial Neural Network" Energies 12, no. 5: 790. https://doi.org/10.3390/en12050790
APA StyleŽnidarec, M., Klaić, Z., Šljivac, D., & Dumnić, B. (2019). Harmonic Distortion Prediction Model of a Grid-Tie Photovoltaic Inverter Using an Artificial Neural Network. Energies, 12(5), 790. https://doi.org/10.3390/en12050790