Estimating PV Module Performance over Large Geographical Regions: The Role of Irradiance, Air Temperature, Wind Speed and Solar Spectrum
Abstract
:1. Introduction
- Some PV module types show variations in module efficiency that are caused by long-term exposure to sunlight and/or high temperatures.
2. Input Data Sets
2.1. Solar Radiation Data
2.2. Ambient Temperature and Wind Speed Data
3. Mathematical Models for PV Performance
3.1. Inclined-Plane Irradiance
3.2. Angle-of-Incidence (AOI) Effects
3.3. Spectral Effects
3.4. Module Temperature
3.5. PV Performance
3.6. Definition of the Module Performance Rati
3.7. Calculation over Large Geographical Areas
- Global inclined irradiance, G
- Global inclined irradiance corrected for AOI effects, Ga
- Spectrally resolved global inclined irradiance, corrected for AOI effects, Ra(λ)
- Module power output for a nominal PV power PSTC = 1 kWp, taking into account AOI, the effects of temperature and low irradiance, but ignoring the effect of wind (essentially setting U1 = 0 in Equation (3)
- Module power output Pw, also taking into account wind speed.
4. Results and Discussion
4.1. Comparison of PV Module Performance Using Measured and Satellite Retrieved Irradiance Data
- Global horizontal and direct horizontal irradiance values (GHI and DHI, respectively)
- Ambient temperature (Tamb)
- Measured–Single location: considering the data from the measured data set (measured irradiance and temperature values) and applying the interpolation method.
- Satellite–Single location: considering the data from the satellite data set (satellite retrieved irradiance values and ambient temperature from ECMWF ERA-interim reanalysis) and applying the interpolation method.
- Satellite–Equation: considering the data from the satellite data set together with temperature data from the ECMWF operational forecast and applying directly Equation (4).
4.2. Calculations of PV Performance over Eurasia and Africa
- North: 60° N
- South: 40° S
- West: 25° W
- East: 115° E
4.3. The Effect of Module Inclination on Module Performance Ratio
4.4. Interannual Variation in MPR
4.5. Influence of Module Type
4.6. Effect of Spectral Variation on the Energy Output of Different Module Types
4.7. Combining All Models
5. Conclusions and Further Work
- PV module reflectivity at shallow angles of incidence (angle-of-incidence effect)
- Effects of variation in the solar spectrum
- Dependence of module efficiency on in-plane irradiance and module temperature
- Effects of irradiance, air temperature and wind speed on the module temperature
- Some new PV module types have special coatings or textured surfaces to reduce the losses due to reflectivity. Measured data from such modules could be used to quantify the improvement in overall PV energy output.
- The method for estimating the spectral effects has so far only considered single-junction PV technologies. Tandem cells and multijunction technologies will require modifications to the methods used here.
- Some PV technologies show long-term variation in the module efficiency. This is especially the case for amorphous silicon technologies. This will require development of models for the behaviour of these modules.
- PV module performance tends to degrade with age, in a way that almost certainly depends on the environmental conditions. Better models for this effect will have to be developed before it is possible to estimate the geographical variation of age-related degradation.
Nomenclature
Acronyms | |
---|---|
AOI | Angle of Incidence |
BSRN | Baseline Surface Radiation Network |
MPP | Maximum Power Point |
STC | Standard Test Conditions |
ECMWF | European Centre for Medium-Range Weather Forecast |
Symbols | |
---|---|
dane (m) | Height above ground of the anemometer measuring wind speed |
dmod (m) | Height above ground of the PV module |
Etot (Wh) | Total energy produced by the module |
Eyear (Wh) | Total yearly energy produced by the module |
⟨ηyear⟩(−) | Annual average module efficiency |
ηSTC (−) | Module efficiency at STC |
GSTC = 1000W · m−2 | In-plane irradiance at STC conditions |
GHI (W · m−2) | Global horizontal irradiance |
DHI (W · m−2) | Direct horizontal irradiance |
G (W · m−2) | In-plane global irradiance |
Ga (W · m−2) | In-plane global irradiance corrected for AOI effects |
Gef f (W · m−2) | In-plane effective global irradiance considering the spectral effects |
H,Ha (kWh · m−2) | In-plane global irradiation over a time period, without and with AOI effects respectively |
Hyear (kWh · m−2) | Total yearly in-plane irradiation |
R(λ) (W · m−2 · nm−1) | Spectral irradiance at wavelength λ |
RSTC (λ) (W · m−2 · nm−1) | Spectral irradiance at STC at wavelength λ |
Ra(λ) (W · m−2 · nm−1) | Spectral global inclined irradiance corrected for AOI effects |
Sr(λ) (AW−1) | Spectral response of the PV module at wavelength λ |
MPR (−) | Module Performance Ratio |
MPRyear (−) | Annual average Module Performance Ratio |
MPRW,year (−) | Annual average Module Performance Ratio considering wind effects |
Pw (W) | Estimated module power considering wind effects |
PSTC (W) | Module power at STC |
U0(W·°C−1·m−2) | Coefficient for module temperature model |
U1(Ws°C−1·m−3) | Coefficient for module temperature model |
k1 to k6 | Coefficients for the PV performance model |
Tamb (°C) | Ambient (air) temperature |
Tmod (°C) | Module temperature |
Wane (ms−1) | Wind speed at the height of the anemometer |
Wmod (ms−1) | Wind speed at the height of the PV module |
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Module Type | U0 | U1 |
---|---|---|
c-Si | 26.9 | 6.20 |
CdTe | 23.4 | 5.44 |
Module Type | c-Si | CdTe |
---|---|---|
k1 | −0.017237 | −0.046689 |
k2 | −0.040465 | −0.072844 |
k3 | −0.004702 | −0.002262 |
k4 | 0.000149 | 0.000276 |
k5 | 0.000170 | 0.000159 |
k6 | 0.000005 | −0.000006 |
Location | Coordinates | Year |
---|---|---|
Cabauw (The Netherlands) | 51.97° N, 4.93° E | 2010 |
Carpentras (France) | 44.08° N, 5.05° E | 2010 |
Cener (Spain) | 42.82° N, 1.60° W | 2010 |
Payerne (Switzerland) | 46.82° N, 6.95° E | 2010 |
Sede Boqer (Israel) | 30.87° N, 34.78° E | 2010 |
Gobabeb (Namibia) | 23.57° S, 15.01° E | 2013 |
MPR Station | Crystalline silicon
| Cadmium Telluride
| ||||
---|---|---|---|---|---|---|
Measured Interpolation | Satellite Interpolation | Satellite Equation | Measured Interpolation | Satellite Interpolation | Satellite Equation | |
Cabauw | 0.926 | 0.933 | 0.926 | 0.915 | 0.921 | 0.913 |
Carpentras | 0.923 | 0.936 | 0.921 | 0.932 | 0.937 | 0.928 |
Cener | 0.921 | 0.929 | 0.928 | 0.926 | 0.929 | 0.927 |
Payerne | 0.925 | 0.930 | 0.927 | 0.925 | 0.923 | 0.920 |
Sede Boqer | 0.895 | 0.897 | 0.893 | 0.921 | 0.923 | 0.921 |
Gobabeb | 0.888 | 0.883 | 0.882 | 0.920 | 0.917 | 0.915 |
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Huld, T.; Amillo, A.M.G. Estimating PV Module Performance over Large Geographical Regions: The Role of Irradiance, Air Temperature, Wind Speed and Solar Spectrum. Energies 2015, 8, 5159-5181. https://doi.org/10.3390/en8065159
Huld T, Amillo AMG. Estimating PV Module Performance over Large Geographical Regions: The Role of Irradiance, Air Temperature, Wind Speed and Solar Spectrum. Energies. 2015; 8(6):5159-5181. https://doi.org/10.3390/en8065159
Chicago/Turabian StyleHuld, Thomas, and Ana M. Gracia Amillo. 2015. "Estimating PV Module Performance over Large Geographical Regions: The Role of Irradiance, Air Temperature, Wind Speed and Solar Spectrum" Energies 8, no. 6: 5159-5181. https://doi.org/10.3390/en8065159