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Porównanie metod MPPT paneli fotowoltaicznych (P&O, IC, Fuzzy Logic) w środowisku Matlab Simulink

Surma P.

Przegląd Elektrotechniczny

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2014

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R. 90, nr 1

66--69

PL

Wiele technik śledzenia maksymalnego punktu pracy (MPPT) paneli fotowoltaicznych zostało do tej pory opracowanych. Jednakże najbardziej powszechne metody to: P&O (Perturb and Observe) , IC (Incremental Conductivity) oraz Fuzzy Logic. W artykule tym zaprezentowano porównanie metod P&O, IC oraz Fuzzy Logic pod względem sprawności działania przy zmieniających się warunkach nasłoneczniania oraz stałej temperaturze pracy.

EN

Many techniques for tracking the maximum power point (MPPT) of photovoltaic panels have been developed so far. However, the most common methods are: P & O (perturb and Observe), IC (Incremental Conductivity) and Fuzzy Logic. This article presents a comparison between P&O and Fuzzy Logic methods in terms of efficiency, when changing some weather conditions at a constant temperature.

2

Porównanie i analiza możliwości wykorzystania algorytmów MPPT dla paneli fotowoltaicznych z wykorzystaniem różnych profili nasłonecznienia

Staniak P., Iwański G., Moćko W., Ornowski M.

Elektronika : konstrukcje, technologie, zastosowania

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2014

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Vol. 55, nr 9

142-146

PL

Artykuł przedstawia porównanie algorytmów MPPT dla źródeł fotowoltaicznych. Do badań wybrano trzy najczęściej wykorzystywane algorytmy. Przedstawiono ich krótką charakterystykę wraz ze strukturą graficzną. Następnie pokazano wyniki badań komputerowych oraz na stanowisku laboratoryjnym. W ostatniej części pracy przedstawiono wnioski oraz określono kierunek kontynuacji badań.

EN

The article presents comparison and the study of the maximum power point tracking (MPPT) methods in the different sunshine conditions. The paper shows the simulation studies and the laboratory tests of three MPPT techniques from the literature, which has been chosen for analysis at the angle of a few aspects e.g. the implementation in the microcontrollers system. The short description of the MPPT techniques is included and the authors present all algorithms, which have been implemented in the microcontroller. In the last part of the article the summary is presented.

3

Optimizing the operation of a photovoltaic generator by a genetically tuned fuzzy controller

Drir N, Barazane L., Loudini M.

Archives of Control Sciences

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2013

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Vol. 23, no. 2

145--167

EN

This paper presents design and application of advanced control scheme which integrates fuzzy logic concepts and genetic algorithms to track the maximum power point in photovoltaic system. The parameters of adopted fuzzy logic controller are optimized using genetic algorithm with innovative tuning procedures. The synthesized genetic algorithm which optimizes fuzzy logic controller is implemented and tested to achieve a precise control of the maximum power point response of the photovoltaic generator. The performance of the adopted control strategy is examined through a series of simulation experiments which prove good tracking properties and fast response to changes of different meteorological conditions such as isolation or temperature.

4

Evaluation of maximum power point tracking methods for photovoltaic systems

Talha A., Boumaaraf H., Bouhali O.

Archives of Control Sciences

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2011

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Vol. 21, no. 2

151-165

EN

The output characteristics of photovoltaic (PV) arrays are nonlinear and change with the solar irradiance and the cell's temperature. Therefore, a maximum power point tracking (MPPT) technique is needed to draw peak power from the solar array to maximize the produced energy. Among the hill climbing methods, the perturb and observe (P&O) method tracks the maximum power point (MPP) by repeatedly increasing or decreasing the output voltage at the MPP of the PV module. The implementation of the method is relatively simple, but it cannot track the MPP when the irradiance varies quickly with time. In addition, itmay cause system oscillation around the peak power points due to the effect of measurement noise. The incremental conductance (IncCond) method is also often used in PV systems. This method tracks the MPPs by comparing the incremental and instantaneous conductances of the solar array. This method requires longer conversion time, and a large amount of power loss results. In addition, extra hardware circuitry is required to implement the system. In this paper, it is shown that the negative effects associated with such a drawback can be greatly reduced if the intelligent method is used to improve P&O and IncCond algorithms. The perturbation step is continuously approximated by using fuzzy logic controller (FLC). By the digital simulation, the validity of the proposed control algorithm is proved.