scholarly journals Maximum Power Point Tracker Controller Using Fuzzy Logic Control with Battery Load for Photovoltaics Systems

2021 ◽  
Vol 12 (10) ◽  
pp. 163-181
Author(s):  
Mazen Yeselam Baramadeh ◽  
Mohamed Abd Almonem Abouelela ◽  
Saad Mubarak Alghuwainem
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Maximum Power Point Tracker ◽  
Logic Control ◽  
Power Point

scholarly journals Comparative analysis of Maximum Power Point Tracking Algorithms for Photovoltaic Applications

2020 ◽  
Vol 15 ◽  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Logic Control ◽  
Power Point

Currently, photovoltaic system has gained importance in electrical power generation system, since it is a clean and renewable energy source. An important characteristic of photovoltaic panels is that the available maximum power is provided only in a single operating point called maximum power point. But the position of maximum power point is not fixed and it moves according to the varying irradiance, varying temperature and the load. This requires a mechanism called maximum power point tracking (MPPT) so that maximum power is obtained effectively. In the literature, many classical methods have been developed and implemented to track the maximum power point. The main objective of this paper is to study and analyze the classical techniques such as Perturb and Observe (P&O), Incremental Conductance (IC) and Fuzzy Logic Control (FLC) algorithms and propose an Adaptive Fuzzy Logic Control (AFLC) for MPPT. The performance of AFLC is compared with the conventional MPPT techniques for varying irradiance. The significance of these methods are studied by implementing the algorithm in MATLAB. The experimental results show the effectiveness and feasibility of the proposed method and the results are verified. The results reveal that the adaptive FLC can quickly track change of MPP for various light intensity and delivers higher power compared to the classical algorithms.

Maximum power point tracking using fuzzy logic control

2012 ◽  
Vol 39 (1) ◽  
pp. 21-28 ◽  
Author(s):  
Mohamed M. Algazar ◽  
Hamdy AL-monier ◽  
Hamdy Abd EL-halim ◽  
Mohamed Ezzat El Kotb Salem
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Logic Control ◽  
Power Point

scholarly journals Fuzzy Logic Control for the tracking of maximum power point of a PV system

2011 ◽  
Vol 6 ◽  
pp. 633-642 ◽  
Author(s):  
F. Bouchafaa ◽  
I. Hamzaoui ◽  
A. Hadjammar
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Logic Control ◽  
Power Point

scholarly journals A NOVEL ENHANCED MPPT METHOD COMBINING FRACTIONAL-ORDER AND FUZZY LOGIC CONTROL

2020 ◽  
Vol 4 (5) ◽  
pp. 22-28
Author(s):  
VIJAYA KUMAR S ◽  
MADHU SUDHAN REDDY M
Keyword(s):  
Fuzzy Logic ◽  
Fractional Order ◽  
Fuzzy Logic Control ◽  
Maximum Power ◽  
Tracking Accuracy ◽  
Pv System ◽  
Maximum Power Point ◽  
Logic Control ◽  
Alpha Factor ◽  
Power Point

A fractional-order fuzzy logic control (FOFLC) method for maximum power point tracking (MPPT) in a photovoltaic (PV) system is presented. By combining the robustness of fuzzy logic with the accuracy of fractional order, the proposed method can improve the tracking accuracy in weather variations compared with the conventional fuzzy MPPT. First, the fractionalorder factor is carefully selected according to the dynamic range of the fuzzy controller. It takes a bigger alpha factor in the first place to expand the fuzzy domain and shortens the time of searching for the MPP. When the maximum power point is approached, it uses a smaller the alpha factor to contract the fuzzy domain and eliminates the oscillations at the MPP. Therefore, the FOFLC in a PV system has rapid dynamic responses under environment variations and high tracking accuracy of the maximum power point. Second, MATLAB/Simulink software is employed to simulate a PV power system and verify the proposed algorithm by various simulations. The enhanced MPPT algorithm has been implemented on a field programmable gate array (FPGA) board. Finally, a boost dc–dc converter experiment has been carried out to evaluate the system performance. The simulation and experiment results show that this method can improve the transient and steady-state performance simultaneously.

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