A Method to Improve the Accuracy of Simulation Models: A Case Study on Photovoltaic System Modelling
<p>Ideal single diode equivalent circuit of a photovoltaic cell [<a href="#B7-energies-14-00372" class="html-bibr">7</a>,<a href="#B8-energies-14-00372" class="html-bibr">8</a>].</p> "> Figure 2
<p>Electrical properties of the solar cells when exposed to solar irradiance.</p> "> Figure 3
<p>Equivalent circuit (Single diode) of a photovoltaic cell [<a href="#B7-energies-14-00372" class="html-bibr">7</a>,<a href="#B8-energies-14-00372" class="html-bibr">8</a>].</p> "> Figure 4
<p>Influence of the series resistance on the solar cell output properties.</p> "> Figure 5
<p>Effect of solar irradiance on the solar cells [<a href="#B7-energies-14-00372" class="html-bibr">7</a>,<a href="#B8-energies-14-00372" class="html-bibr">8</a>].</p> "> Figure 6
<p>Effect of temperature on the solar cells [<a href="#B7-energies-14-00372" class="html-bibr">7</a>,<a href="#B8-energies-14-00372" class="html-bibr">8</a>].</p> "> Figure 7
<p>Structure of the Preciseness Function Learning Model (PFL Model).</p> "> Figure 8
<p>Example of a database of the model with curve-fitting in various forms.</p> "> Figure 9
<p>Learning method structure of the preciseness function learning model (PFL Model).</p> "> Figure 10
<p>Structure of the photovoltaic simulation model with preciseness function learning model (PFL model).</p> "> Figure 11
<p>Accuracy improvement of the proposed model.</p> "> Figure 12
<p>Simulation result of the accuracy improvement.</p> "> Figure 13
<p>The proposed model and the measured data of the PV power output on a cloudy day (<b>a</b>) and a sunny day (<b>b</b>).</p> "> Figure 14
<p>The proposed model and the measured data of the PV power output in the three seasons. (<b>a</b>) In the summer; (<b>b</b>) in the rainy season; (<b>c</b>) in the winter.</p> "> Figure 15
<p>Comparison of the PV energy of the simulated and measured data of the different seasons.</p> "> Figure 16
<p>Comparison of the PV energy of the simulated and measured data of the different seasons.</p> ">
Abstract
:1. Introduction
2. Materials and Methods of the PV System Simulation Model
2.1. Proposed Model for Accuracy Improvement (Interactive Curve Fitting)
2.2. One Diode Equivalent Circuit
2.3. Effects of the Series Resistance and Parallel Resistance of Solar Cells
2.4. Effect of Solar Irradiance on the Solar Cells
2.5. Effect of Temperature on the Solar Cells
2.6. Equation Using for PV Simulation Model
3. Method of Accuracy Improvement
3.1. Preciseness Function Learning Model (PFL Model)
3.2. Photovoltaic System Simulation Model with Preciseness Function Learning Model (PFL Model)
- Part 1: Photovoltaic simulation model, which has two inputs (solar irradiance and module temperature) and one output (PV power).
- Part 2: Improving the accuracy of the photovoltaic simulation model’s output by the proposed model (Preciseness Function Learning Model (PFL Model)).
4. Evaluate Results and Discussions
4.1. Information and Simulation of the PV System
4.2. Daily PV System Simulation
4.3. Seasonal PV System Simulation
4.4. Comparison with the PV Model with the Weight Function
5. Conclusions
Author Contributions
Funding
- Thailand’s National Electronics and Computer Technology Center.
- Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang.
- Thailand Graduate Institute of Science and Technology, Scholarship recipient code TG-44-22-59-016D.
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
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PV Technology | Values |
---|---|
Monocrystalline | 1.2 |
Polycrystalline | 1.3 |
CdTe | 1.5 |
CIS | 1.5 |
GaAs | 1.3 |
Amorphous silicon single junction | 1.8 |
Amorphous silicon double junction | 3.3 |
Amorphous silicon triple junction | 5.0 |
Types | Functions |
---|---|
Exponential | |
Fourier | |
Gaussian | |
Linear | |
Polynomial | |
Sum of sine |
Curve Fitting Types | R-Square |
---|---|
Exponential | 0.9029 |
Fourier | 0.9996 |
Gaussian | 0.9829 |
Linear | 0.9987 |
Polynomial | 0.9993 |
Sum of Sine | 0.9987 |
Curve Fitting Types | R-Square |
---|---|
Exponential | 0.9119 |
Fourier | 0.9996 |
Gaussian | 0.9861 |
Linear | 0.9946 |
Polynomial | 0.9993 |
Sum of Sine | 0.9994 |
PV Systems | Rate Capacity | Panels | Number of PV Panel |
---|---|---|---|
Thailand (Central region) | 12 MW | 245 Wp | 48,980 |
Parameters of PV Panel | Value and Units |
---|---|
Rated Power of PV Panel, Pm | 245 Wp |
Open Circuit Voltage of PV Panel, Voc | 37.1 V |
Short Circuit Current of PV Panel, Isc | 8.8 A |
Maximum Power Voltage of PV Panel, Vm | 30.1 V |
Maximum Power Current of PV Panel, Im | 8.14 A |
Ideality factor of PV Panel (n)—Poly Crystalline [18] | 1.3 |
Case Day | Measured Data (MW) | Proposed Model (MW) | nRMSE (Normalized RMSE) |
---|---|---|---|
Sunny Day | 71.43 | 72.70 | 1.79 |
Cloudy Day | 64.57 | 66.63 | 3.19 |
Data | 2018 | 2019 | 2018–2019 | ||||||
---|---|---|---|---|---|---|---|---|---|
Summer | Rainy | Winter | Average | Summer | Rainy | Winter | Average | Average | |
Measured Data (MW) | 1556 | 1347 | 1610 | 1504 | 1606 | 1589 | 1157 | 1450 | 1477 |
Proposed Model (MW) | 1591 | 1342 | 1615 | 1516 | 1637 | 1583 | 1141 | 1453 | 1485 |
nRMSE (Normalized RMSE) | 2.43 | 0.39 | 0.75 | 1.19 | 1.81 | 0.59 | 1.40 | 1.26 | 1.23 |
Data | Proposed Model | PV Model with Weight Func. | ||||||
---|---|---|---|---|---|---|---|---|
Summer | Rainy | Winter | Average | Summer | Rainy | Winter | Average | |
Measured Data (MW) | 1606 | 1589 | 1157 | 1450 | 1606 | 1589 | 1157 | 1450 |
Simulation Data (MW) | 1637 | 1583 | 1141 | 1453 | 1564 | 1543 | 1124 | 1410 |
nRMSE (Normalized RMSE) | 1.81 | 0.59 | 1.40 | 1.26 | 2.63 | 2.89 | 2.88 | 2.80 |
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Bupi, A.; Kittisontirak, S.; Chinnavornrungsee, P.; Songtrai, S.; Manosukritkul, P.; Sriprapha, K.; Titiroongruang, W.; Niemcharoen, S. A Method to Improve the Accuracy of Simulation Models: A Case Study on Photovoltaic System Modelling. Energies 2021, 14, 372. https://doi.org/10.3390/en14020372
Bupi A, Kittisontirak S, Chinnavornrungsee P, Songtrai S, Manosukritkul P, Sriprapha K, Titiroongruang W, Niemcharoen S. A Method to Improve the Accuracy of Simulation Models: A Case Study on Photovoltaic System Modelling. Energies. 2021; 14(2):372. https://doi.org/10.3390/en14020372
Chicago/Turabian StyleBupi, Aekkawat, Songkiate Kittisontirak, Perawut Chinnavornrungsee, Sasiwimon Songtrai, Phassapon Manosukritkul, Kobsak Sriprapha, Wisut Titiroongruang, and Surasak Niemcharoen. 2021. "A Method to Improve the Accuracy of Simulation Models: A Case Study on Photovoltaic System Modelling" Energies 14, no. 2: 372. https://doi.org/10.3390/en14020372