Comparison of Two Common Maximum Power Point Trackers by Simulating of PV Generators

Zégaoui, Abdallah; Aillerie, Michel; Petit, Pierre; Sawicki, Jean-Paul; Jaafar, Ali; Salame, Chafic; Charles, J.‐P.

doi:10.1016/j.egypro.2011.05.077

Cited by 51 publications

(27 citation statements)

References 7 publications

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“…Thus, for a PV module comprised of cells in series and parallel, the equation is expressed as below (Golder 2006), (Zegaoui et al 2011), (Nafeh 2010):…”

Section: Mathematical Modelling Of Pv Modulementioning

confidence: 99%

Artificial neural network based maximum power point tracking controller for photovoltaic standalone system

Khanaki

Radzi

Marhaban

2014

International Journal of Green Energy

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This paper presents a two-stage maximum power point tracking (MPPT) controller using Artificial Neural Network (ANN) for photovoltaic (PV) standalone system, under varying weather conditions of solar irradiation and module temperature. At the first-stage, the ANN algorithm locates the maximum power point (MPP) associated to solar irradiation and module temperature. Then, a simple controller at the second-step, by changing the duty cycle of a DC-DC boost converter, tracks the MPP. In this method, in addition to experimental data collection for training the ANN, a circuit is designed in MATLAB-Simulink to acquire data for whole ranges of weather condition. The whole system is simulated in Simulink. Simulation results show small transient response time, and low power oscillation in steady-state. Furthermore, dynamic response verifies that this method is very fast and precise at tracking the MPP under rapidly changing irradiation, and has very low power oscillation under slowly changing irradiation. Experimental results are provided to verify the simulation results as well.

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“…Thus, for a PV module comprised of cells in series and parallel, the equation is expressed as below (Golder 2006), (Zegaoui et al 2011), (Nafeh 2010):…”

Section: Mathematical Modelling Of Pv Modulementioning

confidence: 99%

Artificial neural network based maximum power point tracking controller for photovoltaic standalone system

Khanaki

Radzi

Marhaban

2014

International Journal of Green Energy

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“…When the temperature is constant, the maximum power point of photovoltaic cells under different irradiance distribution on a straight line approximately, that is the maximum power point of pv cells similar at a constant voltage m U [9][10][11]. The relationship between m U and oc U is given by:…”

Section: Mppt Control Algorithmsmentioning

confidence: 99%

Study of the Maximum Power Point Tracking Method for photovoltaic system

Liu¹,

Zhang²

2017

Proceedings of the 2017 6th International Conference on Energy and Environmental Protection (ICEEP 2017)

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Abstract. In this paper, the influence of serial resistance Rs and shunt resistance Rsh for PV cells are studied. The series resistance Rs has a great influence on the output characteristics of the PV cells. Therefore, it is particularly important to solve the value of Rs for the model of solar cells. Rsh is very large, in the process of PV modular modeling, the value of Rsh can be neglected. Maximum power point tracking(MPPT) algorithms play an important role in the optimization of the power and the efficiency of a photovoltaic(PV) generation system. According to the contradiction of the classical Perturb and Observe(P&O) method between the corresponding speed and the tracking accuracy on steady-state, an improved MPPT method has been put forwarded in this paper. According to establishing control model and using MATLAB/Simulink to simulate the main circuit and control system, we made the comparison among P&O method and improved P&O method. In particular, this study compares the behaviors of each technique in presence of solar irradiation variations.We have also compared the output power of the system with two MPPT method.

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“…For further studies in applications of converters mainly dedicated to renewable energy systems that take into consideration the present modeling approach, one can read recent articles presenting practical realizations and developments of DC-DC converters integrated in photovoltaic generators [53,54]. Nevertheless, this point is out of the scope of this work, and one can also refer to numerous articles in literature, some of them are given in the references [55][56][57][58].…”

mentioning

confidence: 99%

Efficiency of magnetic coupled boost DC‐DC converters mainly dedicated to renewable energy systems: influence of the coupling factor

Petit

Aillerie

Salame

et al. 2014

Circuit Theory & Apps

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International audienceThis paper presents a specific analysis of an individual basic magnetically coupled direct current-to-direct current (DC–DC) converter specially designed for integration in a distributed architecture of renewable energy generators for smart grid applications. In such distributed architecture dedicated for renewable energy, parallel high-voltage DC presents many advantages over the classical centralized one. We show that in such setup, high voltage can be advantageously produced using a specific magnetically coupled boost converter, and we point out the influence of the coupling factor, generally considered equal to one, on the overall performance of the converter and on the global energy efficiency of the installation. In this study, the generalized concepts of system energy parameters of DC–DC converters are introduced and applied to the transient analysis. Consequently, the operation of a magnetic coupled DC–DC converter with a recovery stage is modeled. The simulation results are compared with those of the behavioral study, deduced from the model pointing out the large influence of the coupling factor value on the global behavior and mainly on the value of the recovery voltage, in all the various parts of the switching cycle. The renewable energy generator operating parameters, such as current and voltage values, can then be predicted in a more useful way to compute new similar DC–DC converter systems

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Comparison of Two Common Maximum Power Point Trackers by Simulating of PV Generators

Abstract: International audienc

Cited by 51 publications

References 7 publications

Artificial neural network based maximum power point tracking controller for photovoltaic standalone system

Artificial neural network based maximum power point tracking controller for photovoltaic standalone system

Study of the Maximum Power Point Tracking Method for photovoltaic system

Efficiency of magnetic coupled boost DC‐DC converters mainly dedicated to renewable energy systems: influence of the coupling factor

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