PV panel modeling with improved parameter extraction technique

Rasool, Fahad; Drieberg, Micheal; Badruddin, Nasreen; Singh, Balbir Singh Mahinder

doi:10.1016/j.solener.2017.05.078

Cited by 38 publications

(32 citation statements)

References 31 publications

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“…Based on Equation 2, the temperature of cell affects the voltage and by considering Equations 1 and 4 it will affect the fill factor (FF) of the cell. 40 The current-voltage relationship in a two-diode model is represented as Equation 7. Figure 3 shows the electrical behavior of a crystalline silicon solar cell by a typical ideal single diode equivalent circuit.…”

Section: Models For First Generationmentioning

confidence: 99%

“…This current is related to recombination of mobile charge carriers and leads to decrease the output current. 40 The current-voltage relationship in a two-diode model is represented as Equation 7. Also, in this model, the diode saturation current (I 0 ) that is related to temperature can be shown as Equation 8.…”

Section: Models For First Generationmentioning

confidence: 99%

“…Adopted from Rasool et al40 Copyright (2018), with permission from Elsevier F I G U R E 2 I-V and P-V curves of various irradiance levels for a typical photovoltaic (PV) cell at 25°C. Adopted from Rasool et al40 Copyright (2018), with permission from Elsevier F I G U R E 2 I-V and P-V curves of various irradiance levels for a typical photovoltaic (PV) cell at 25°C.…”

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confidence: 99%

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Generation and combination of the solar cells: A current model review

Khatibi

Astaraei

Ahmadi

2019

Energy Science & Engineering

104

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Generally, first and second generations of photovoltaic (PV) cells are including mono‐crystalline silicon, amorphous silicon, and dye‐synthesized solar cells. Investigating the electrical current behavior of these sorts of PV cells shows that a modified multi‐ or single diode(s) model with shunt and series resistance can use as a good choice in a specific range of the current. For other constructions such as multi‐junction PV cells that consist of the third generation, the network models are the best choice. Also, the network models can be used for the first and second generations to improve the validity of model in the wider range of current. In addition to existing generations, PV array and modules, which are serial and parallel arrays of PV cells, will lead to a higher current or voltage. The main disadvantage of using these sorts of systems is their more space occupation. This problem can be solved by using the concentrated PV (CPV) systems that focus the received irradiation on a smaller surface. By considering the generated current, voltage, power, temperature effect, and financial analysis, it seems third‐generation PV systems are more efficient among all the generations. Finally, by considering the ratio of generated current on the occupied space, the CPV systems will be a better choice.

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Section: Models For First Generationmentioning

confidence: 99%

Section: Models For First Generationmentioning

confidence: 99%

mentioning

confidence: 99%

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Generation and combination of the solar cells: A current model review

Khatibi

Astaraei

Ahmadi

2019

Energy Science & Engineering

104

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“…In [11], the 1M5P model is applied for outdoor lighting using a polycrystalline PV panel through the Improved Parameter Extraction Technique (IPET). The open circuit point and short circuit point is used to extract the values of Iph and Io.…”

Section: Related Workmentioning

confidence: 99%

“…In [13], a monocrystalline PV panel was used for indoor lighting energy harvesting system. Similar to [11], the parameters α, Io, Iph and Rs are obtained by through the open circuit point, short circuit point and maximum power point method. However, the value of R p in [13] was neglected.…”

Section: Related Workmentioning

confidence: 99%

Modelling of Indoor Light Energy Harvesting for IoT

Ragunathan

Drieberg

Aziz

et al. 2019

International Journal of Simulation: Systems, Science &Amp; Technology

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Network communications have been evolving with the rise of the Internet of Things (IoT). Low powered IoT devices, which consume less power, can be powered up using an energy harvesting system instead of batteries. Due to the wide availability of indoor lighting in offices, homes, factories, malls and hospitals, energy can be harvested through these sources. A photovoltaic panel that converts light energy into electrical energy is used to harvest the power from these indoor lighting. However, most manufacturers provide datasheet values only at limited values of illuminance. Thus, it is important to have an accurate model of photovoltaic panel that can predict and estimate its performance at all operating conditions. This paper presents the methodology for modelling an accurate Single Mechanism Five Parameter (1M5P) model for indoor light energy harvesting. The accuracy of the model is highly dependent on the parameter extraction technique used. A high accuracy technique for outdoor was adapted for the indoor application. An experiment was also undertaken to determine the equivalent irradiance for different values of illuminance. The proposed model was applied on a commercial PV panel and its I V and P-V curves were obtained. Then, a controlled experiment is carried out with the PV panel under the indoor light condition. The results for both the model and experiment were compared, and they were found to be in good agreement, thus validating the accuracy of the proposed model.

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