Mathematical modeling of photovoltaic cell/module/arrays with tags in Matlab/Simulink

Nguyen, Xuan Hieu; Nguyễn, Minh Phương

doi:10.1186/s40068-015-0047-9

Cited by 224 publications

(84 citation statements)

References 2 publications

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“…Mathematical modeling of photovoltaic cells is being continuously updated to enable researchers to have a better understanding of its working. The models differ depending on the types of software researchers used such as MATLAB® [8]. A function in MATLAB® environment has been developed to calculate the current output from data of voltage, solar irradiance and temperature in the study of Gonzaez-Longatt (2005) [9].…”

Section: -Methodologymentioning

confidence: 99%

“…Where 0 is the reverse saturation current of diode, a is ideality factor of the diode, V is the voltage across the diode, and = is termed as thermal voltage due to its substantial temperature dependence, Ns is the number of photovoltaic cells modules connected in series, =1.381×10 -23 J/K is the Boltzmann's constant), e = 1.602×10 -19 C is the electron charge, T is the junction temperature (operating temperature) in Kelvin (K). The photo-current ℎ is generated on absorption of solar irradiance by solar cell hence photo-current value is directly related to variation in solar irradiance and temperature and that is [8,22,23]:…”

Section: -Methodologymentioning

confidence: 99%

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Modeling and Simulation of the Photovoltaic Cells for Different Values of Physical and Environmental Parameters

Hysa

2019

Emerg Sci J

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Both research and technological development in the area of renewable energy sources are necessary to account for the increase in energy demand and environment problems in the world. The photovoltaic (PV) cell has been described by non-linear outputs characteristics in current-voltage and power-voltage. This outputs is affected by various effects such as; series resistance ( ), shunt resistance ( ℎ ), solar irradiance and temperature. In this paper the effect of variation of parameters has been studied such as series resistance ( ) and shunt resistance ( ℎ ) of the diode in the photovoltaic cell and these effects could be seen in the Current-Voltage (I-V) and Power-Voltage (P-V) characteristic curves. In this paper also has been studied the effect of variation of the environmental parameters such as solar irradiance and temperature. Results show that a higher temperature at constant solar irradiance produces a decrease power. So the voltage and the photovoltaic cell output power tend to decrease at higher temperatures, but there is no noticeable effect on the photovoltaic cell current. Thus, it is important to keep the cell temperature as low as possible, because higher temperatures have negative effect on output power of photovoltaic cell. On the other hand, the effect of solar irradiance on photovoltaic cell, it reveals that higher solar irradiance gives higher current and higher power. Shunt resistance has significant effect on the operating characteristic curves of PV cells as low power output is recorded if the value of shunt resistance varies from 0.07 ohms to 1700 ohms. Finally, I have presented power-voltage characteristic curves and current voltage characteristic curves of photovoltaic cell for different solar irradiance in Shkoder, Tirana and Vlore.

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Section: -Methodologymentioning

confidence: 99%

Section: -Methodologymentioning

confidence: 99%

Modeling and Simulation of the Photovoltaic Cells for Different Values of Physical and Environmental Parameters

Hysa

2019

Emerg Sci J

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“…We must convert the solar radiation into power for the PV and heat for the solar collector. For the PV, we use the approach from Nguyen and Nguyen with V = V mp ; we replace equation 3 of Nguyen and Nguyen by equation 9 of De Soto et al For the cell temperature, we use the approach from Duffie and Beckman ,. section 23.3 For the solar collector, we use the collector‐efficiency equations from Duffie and Beckman, Chapters 3–6 with the factor F' = 0.8, the temperature of the plates equal to the outside temperature, and the difference of temperature between the plates and glass set to 20° C. All the layers of glass have the same temperature, and the inlet water comes from the street.…”

Section: Mathematical Modelsmentioning

confidence: 99%

A realistic energy optimization model for smart‐home appliances

2019

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Summary Smart homes have the potential to achieve optimal energy consumption with appropriate scheduling. The control of smart appliances can be based on optimization models, which should be realistic and efficient. However, increased realism also implies an increase in solution time. Many of the optimization models in the literature have limitations on the types of appliances considered and/or their reliability. This paper proposes a home energy management scheduling model that is more realistic and efficient. We develop a mixed integer linear optimization model that minimizes the energy cost while maintaining a given level of user comfort. Our main contribution is the variety of specific appliance models considered and their integration into a single model. We consider the use of energy in appliances and electric vehicles (EVs) and take into account renewable local generation, batteries, and demand response. Our models of a shower, a fridge, and a hybrid EV consider both the electricity consumption and the conventional fuel cost. We present computational results to validate the model and indicate how it overcomes the limitations of other models. Our results, compared with the best competitors, provide cost savings ranging from 8% to 389% over a horizon of 24 hours.

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“…Nguyen and Nguyen [19] proposed a robust PV model built with tag tools in Simulink environment. They assumed a very small value for R s , that is 0.0001 Ω , and a large value for R sh , that is 1000 Ω .…”

Section: Introductionmentioning

confidence: 99%

A simple approach to extract the unknown parameters of PV modules

Hussein¹

2017

Turk J Elec Eng & Comp Sci

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are not provided by most manufacturers. Since these parameters are crucial for PV module characterization, our study presents an exact, closed-form expression for Rs that is solvable numerically while increasing the value of the ideality factor ( a) in small increments, so that four equations are formulated to compute the unknown parameters. To validate the proposed approach, a set of I − V curves were computed for different values of a , and these results were compared alongside corresponding reference data for the BP SX150 and MSX60 PV modules. Average RMS errors of 0.035 for BP SX150 and 0.014 for MSX60 between the reference data and the computed data suggest that proposed approach could be used as an alternative method to quantify important missing parameters required for characterization of PV modules.

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Mathematical modeling of photovoltaic cell/module/arrays with tags in Matlab/Simulink

Cited by 224 publications

References 2 publications

Modeling and Simulation of the Photovoltaic Cells for Different Values of Physical and Environmental Parameters

Modeling and Simulation of the Photovoltaic Cells for Different Values of Physical and Environmental Parameters

A realistic energy optimization model for smart‐home appliances

A simple approach to extract the unknown parameters of PV modules

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