IMPACT OF IDEALITY FACTOR AND SEMICONDUCTIONG MATERIAL ON PV MODULE PERFORMANCES
Mahasniza Ibrahimi, S. A. Rahmanii, M. Othmaniii & K. N. Zainul Ariffiniv
ii (Corresponding author). Lecturer, Faculty of Engineering and Built Environment, Universiti Sains Islam Malaysia. [email protected]
i Student, Faculty of Engineering and Built Environment, Universiti Sains Islam Malaysia.
iii Lecturer, Faculty of Engineering and Built Environment Universiti Sains Islam Malaysia.
iv Lecturer, Faculty of Engineering and Built Environment Universiti Sains Islam Malaysia.
Abstract
The photovoltaic (PV) system has drawn worldwide attention for electricity generation over the other conventional power resources since it is clean and renewable. The PV system allows the Sun’s energy to be converted to electricity using solar cells which currently is made by silicon. This project aims to evaluate the impact of ideality factor and semiconducting material variations on the I-V and P-V characteristics of the PV cell. For the purpose, five mathematical equations used to replicate the operations of PV module are modelled in MATLAB/SIMULINK and the electrical performances of the PV modules are analyzed. The results indicated that the electrical performances of a PV cell are highly dependent on the types of semiconducting material used and the ideality factor. From the tested material, it is found that at a temperature below the standard temperature condition (STC) of 25°C, Gallium Phosphide, GaP with a bandgap of 2.26eV would be the better option. An improved of 9.52% in maximum power is observed at 10°C when compared to silicon. However, at a temperature above the STC of 25°C, the use of Germanium with a bandgap of 0.67eV would be the better option than silicon as an increased of the maximum power of 4.97% is found at 40°C. Besides, the improper fabrication process (e.g. n= 2.0) would reduce the Pmax of the PV modules by 12%.
Keywords: Photovoltaic Modelling, Material, Renewable, Solar, Semiconductor
INTRODUCTION
Normally, power generation in Malaysia comes from various non-renewable energy resources such as coal, natural gases and fuel oil (Samsudin, et al., 2006). These sources may take thousands or millions of years to be ready and may no longer be available soon as the world is highly dependent on those resources. Therefore, it is obvious that the industry needs to move to clean and renewable energy such as photovoltaic (PV), especially for countries that receive abundant sunlight. Photovoltaic allows the
conversion of solar energy from sunlight into the electricity and it is found to be an effective and environmentally friendly approach. Despite, there is various type of PV cell in the market such as the monocrystalline, polycrystalline, and thin-film type but they are all mainly constructed by using silicon semiconducting material (Afework, et al., 2018). Besides, the pure silicon would typically require 1.11eV of energy to free the electrons in its crystal structure (Anon., n.d.). At present, many countries such as Germany, China, Japan, Italy, and the United State of America have utilised the use of solar energy in their energy production industry (Walton, 2019).
In this paper, factors that influence the operation and electrical performances of photovoltaic systems such as the ideality factor, and semiconductor material are studied. The PV cell circuit is typically made up of diode, hence it becomes the main reason for the impact of ideality factor to be analyzed. Meanwhile, the type of semiconductor materials used in PV module is also expected to affect the electrical PV performance as each of them has different bandgap characteristics. For this, the mathematical equations that replicate the operation of the PV module are modelled in MATLAB. In general, the PV model is developed based on the single diode model with the present of series and shunt resistance in the circuit as it is widely used as the reference by the industry.
PHOTOVOLTAIC MODELS
The photovoltaic cell is made up of semiconductor material that converts the energy received from the sunlight into electricity by using the photovoltaic effect. The effect would allow the generation of electricity as the semiconductor is exposed to sunlight. Alboteanu, Popescu and Piciu, (2007) stated in their article that there are three photovoltaic models and may be simulated by using MATLAB software. The three photovoltaic models include the one-diode model, the two-diode model and the empirical model.
The one-diode model consists of a semiconductor cell and two additional resistances which are identified as the series resistance and shunt resistance as shown
Besides, PV cells work by utilizing the photovoltaic effect which the effect is dependent on the materials of semiconductor used. Different materials may have different sunlight absorption capability which then would influence the electron flow between the two charged layers and thus the overall performance of the PV cell.
Theoretically, as the electrons are expelled from the conduction band due to the absorption of light photons of a certain wavelength, the free electrons will be captured which then produce an electric current. Within the PV cell, some portion of the solar energy is absorbed in the semiconductor material as sunlight reaches its surface (Paul and Kenneth, 1982; Gil Knier, 2011; Abdulkadir, Samosir and Yatim, 2012; Ndiaye et al., 2013; Weidong, 2017).
MODELLING THE PV MODULES
Chtita et al. (2019) has introduced a single diode model of Nanosatellite photovoltaic panel which the triple junction cell has been used in their photovoltaic model. The main purpose for this is to obtain a higher performance of electrical behaviour under the effect of both solar irradiation and temperature. The proposed model shows an adequate accuracy of the electrical curves which is obtained using Psim software. Psim is a simulation software used to simulate any electronic circuit especially suitable for power electronics and motor drive simulation.
Meanwhile, Chouder et al. (2012) has presented the monitoring, modelling and simulation of photovoltaic systems by using LabVIEW software. The term LabVIEW stands for Laboratory Virtual Instrument Engineering Workbench is a visual programming language for application design and software technologies involving evaluating, measuring and controlling with rapid access to hardware and data insight.
The photovoltaic model used in this platform is the one diode model by varying the value of the irradiance and temperature according to the standard condition and based on the value obtained from the industrial datasheet. The study focused on the grid-connected photovoltaic system by considering real conditions of climate parameters.
PV CELL CIRCUIT
In general, the basic PV cell circuit is made up of a collection of PV cell as shown in Figure 7 (Anon., n.d.). There are various components involved in PV cells such as the diode, the series resistance and the shunt resistance.
Figure 7: The circuit of PV cell Parameters
Based on the circuit, there are five parameters need to be considered to replicate the actual operation of the PV cell and this includes the photocurrent, saturation current, ideality factor of the diode, series resistance and shunt resistance. In this study, an approach is presented to calculate all five parameter values numerically minimizing assumptions and simplifications (Ghani et al., 2014; Rusirawan and Farkas, 2014).
METHODOLOGY
Figure 3 indicates the overall process to analyse the characteristics and performance of the PV module in this study. In general, the methodology is classified into five different stages as below:
Figure 8: Flow chart of project methodology
Stage 1: Determining the mathematical equations used to replicate the operations of PV module. The equations are presented as in Table 1:
Table 4: Mathematical equations used to model the PV module Parameter Mathematical Equation Saturation current, Io
Reverse saturation, Irs
Analysis of PV module characteristics and performances using Matlab
Simulink
Determine the mathematical equations used to replicate the operation of a PV
module
Develop the PV module in Matlab/Simulink
Validate the developed model with the industrial data
Simulating PV module performances under different analysis:
• Ideality factor
• Semiconductor material (Band gap)
Conclusion and Recommendation Satisfy
Analysis on the results YES
3 1 1
exp
o n
o rs
n
qEg T T I I T
T nK
æ æ öö
ç ç - ÷÷
æ ö ç è ø÷
= ç ÷è ø çççè ÷÷÷ø
exp 1
rs sc
oc s
I I
qV nN KT
= æ ö
ç ÷-
è ø
Shunt current, Ish
Photo current, Iph
PV current, I
Where:
T is the temperature
q is the electron charge (1.6 x 10-19 Coulomb) Eg0 is the bandgap of the semiconductor n is the ideality factor
K is the Boltzmann constant (1.38 x 10-23 J/K) Isc is the short circuit current (A)
Voc is the open circuit voltage (V) Ns is the number of solar cells in series V is the voltage (V)
I is the current (A)
Rs is the series resistance (Ω) Rsh is the shunt current (Ω)
ki is the short circuit current/temperature coefficient G is the irradiance (W/m2)
Stage 2: Develop PV module by using MATLAB/Simulink
The PV module is modelled by utilizing the Simulink library browser according to the five equations that are previously discussed. Related block model such as add, product, constant, math function, etc is used to develop the PV model equivalent to
sh s
sh
I V IR R
= +
[
( 298)][
/1000]
ph sc i
I = I +k T- G
exp( )( ) 1
ph O s sh
s
I I= -I éêë V IR+ qnKTN - -ùúû I
the exact equations. The complete PV model developed in MATLAB/Simulink is shown as in Figure 4.
Figure 9: The developed PV model in MATLAB/Simulink
The properties of the PV module are declared in the callback function under “InitFcn”
as in Table 2 below;
Table 5: Properties of the PV module
Properties Values
ki 0.0032
q 1.6x10-19 C
K 1.38x10-23 J/K
n 1.3
Eg0 1.11
Rs 0.221 Ω
Rsh 415.405 Ω
Tn 298 T
Voc 32.9 V
Isc 8.21 A
Ns 54
Stage 3: Validate the developed model with the industrial data
The maximum power of the developed PV model which operates at 25 ⁰C and 1000 W/m2 is compared with the industrial datasheet as in Figure 5 (Anon., n.d.). The percentage difference is calculated based on the formula below. It is found that the developed PV module is found to be 80% in agreement with the industrial data.
Figure 10: Industrial Data
Stage 4: Simulation of PV module characteristics and performance under different conditions.
In general, two different case studies are being considered in the study. First is on the impact of the ideality factor (Case study 1) and secondly is related to the impact of using different semiconductor materials (Case study 2). For the analysis, the temperature is varied from 25 ⁰C until 100 ⁰C while the irradiance is fixed at 1000 W/m2.
§ Case study 1: Varying value of ideality factor of the diode in the PV circuit from 1.0 until 2.0
§ Case study 2: Varying the type of semiconductor material used is by varying the value of bandgap energy. Table 3 shows the relationship between the type of semiconductor material used and their bandgap value.
Table 3: List of Semiconductor materials and its bandgap value
Semiconductor Germanium Gallium Gallium
RESULTS AND DISCUSSION
Results and discussion for this research are divided into two subsections as follows:
Study of the ideality factor of diode
The ideality factor changes between one and two depending on the light intensity, and to obtain a meaningful ideality factor, values between 1 and 2 is needed to be normalized.
Figure 11 shows the I-V and P-V curves of the PV module as the ideality factor being varied from 1.0 to 2.0.
Figure 11: The I-V (left) and P-V (right) graphs as ideality factor value being varied Both the I-V and P-V curves shown in
Figure 11 indicates the current-voltage and power-voltage relationships at a constant temperature of 25 ⁰C and irradiance of 1000 W/m2 respectively as the ideality factor increases up to 2.0. Meanwhile, Table 6 detailed out the Imax, Vmax, and the Pmax value extracted from the curves.
Table 7: Impact of ideality factor on the PV module’s electrical performance n Imax (A) Vmax (V) Pmax (W)
1.00 7.761 26.8 208
1.10 7.707 26.6 205
1.20 7.652 26.4 202
1.30 7.634 26.2 200
1.40 7.557 26 197
1.50 7.519 25.8 194
1.60 7.471 25.7 192
1.70 7.461 25.6 191
1.80 7.441 25.4 189
1.90 7.421 25.2 187
2.00 7.360 25 184
The results indicate that the increase of ideality factor value would reduce the value of the Imax and Vmax, which also consequently reduces the Pmax value. The Imax and Vmax are reduced by almost 5.2% and 6.7% respectively as the ideality factor of 2.0 being used as compared to when n = 1.0. In this condition, the PV module would only capable to produce Pmax of 184W which is 12% less than during n = 1.0. Therefore, it is important to ensure that the ideality factor of the semiconductor to be lower as possible (e.g. n= 1.0). This is possible by ensuring a proper fabrication process is done during the manufacturing phase. The improper fabrication process may reduce the performance of the semiconductor thus the PV module.
Study of the material of the semiconductor
In this analysis, four different semiconductor materials are tested, and the electrical performances of the PV module are analyzed. The I-V (left) and P-V (right) curves below show the current-voltage and power-voltage relationships at a constant irradiance value of 1000 W/m2 when Germanium is used as the semiconducting material. Besides, in the analysis, the temperature is varied from 5 ⁰C up to 100 ⁰C.
Material 1: Germanium, Ge with a bandgap energy of 0.67 eV
Figure 13: I-V and P-V Characteristics using Silicon Material 3: Gallium Arsenide, GaAs with a bandgap energy 1.43 eV
Figure 14: I-V and P-V Characteristics using Gallium Arsenide Material 4: Gallium Phosphide, GaP with a bandgap energy of 2.26 eV
25V, 7.520A 7.5V, 5.867A
Figure 15: I-V and P-V characteristics using Gallium Phosphide
Based on the result obtained for the four materials as in Figure 12 to Figure 15, the variation of the Pmax for the PV modules due to the use of different semiconducting material used is summarized as in Figure 16. The figure is used to indicate the Pmax increment or decrement that being recorded at temperatures around (10°C – 40°C) the STC of 25°C for the Germanium, Gallium Arsenide, and Gallium Phosphide in comparison to the Silicon.
-1.46
2.06
4.97
2.56 0.95
-1.06 9.52
3.69
-5 0 5 10 15
10˚C 20˚C
30˚C 40˚C
Pmax increment (%))
T < STC (25˚C) T > STC (25˚C)
* in comparison to silicon
9.52% and 3.69% are found at 10°C and 20°C respectively. The use of Gallium Arsenide, GaAs would also offer Pmax increment up to 2.56% and 0.95% at 10°C and 20°C respectively. However, this is the opposite when Germanium is used as the semiconducting material as Pmax decrement up to 4.11% and 1.46% are found at 10°C and 20°C respectively
At temperature above the STC, the use of Germanium would be the better option as an increment of Pmax up to 2.06% and 4.97% are found at 30°C and 40°C respectively.
The use of Gallium Arsenide, GaAs would result in Pmax increment up to 1.06% and 3.61% at 30°C and 40°C respectively. The decrement is even higher for the Gallium Phosphide (GaP) as Pmax decrement up to 3.83% and 14.67% are recorded at 10°C and 20°C respectively.
In general, the results indicate that the semiconducting material used may have a significant impact on the performance of the PV module. The selection of semiconducting material would be even crucial when the operating temperature conditions play an important role. From the analysis, using a semiconducting material with lower bandgap value would be beneficial at higher temperature condition. This is proven as Germanium with 0.67eV may offer Pmax increment of about 2.06% and 4.97% when compared to Silicon at temperatures of 30°C and 40°C respectively. The increment is also expected to be higher as the temperature increases. However, as the PV module is operating at a lower temperature, the semiconducting material such as Gallium Arsenide, GaAs and Gallium Phosphide, GaP with higher bandgap value would be the better option. This finding may be beneficial in the discovery of new materials to improve the performance of the PV module.
CONCLUSION
This project has successfully performed the modelling of PV module using the MATLAB/SIMULINK tool. The analysis has highlighted the impact of ideality factor and semiconducting material used for the PV modules on their performances. The results indicate that the improper fabrication process may result in the degradation of PV module performance. With a proper fabrication process, the semiconductor may imitate perfectly operation of the ideal diode which this when the ideality factor, n is equal to 1.0. In the worst-case scenario, the reduced performance of 12% (as n= 2.0) may be found as the result of the improper fabrication process. The semiconducting material would also need to be carefully chosen to ensure maximum power delivery from the PV module is available. The used of other material than Silicon such as Germanium may offer improved electrical output from the PV module particularly at a higher temperature.
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