Modelling and Simulation of Boost Converter with Maximum Power Point Tracking (MPPT) for Photovoltaic Application

2014 ◽  
Vol 71 (5) ◽  
Author(s):  
Ahmad Shaharuddin Mat Su, ◽  
Rasli Abd Ghani ◽  
Slamet Slamet
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Maximum Power Point Tracking ◽  
Boost Converter ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Proposed Model ◽  
Power Point

This paper presents the proposed model and simulation of a DC to DC converter with maximum power point tracking (MPPT) using fuzzy logic controller (FLC) for a standalone Photovoltaic (PV) System. This research will focus on the developing high performance DC to DC converter with fuzzy logic controller based to extract the maximum power that generated by the PV panel. The system composed of the PV array and DC-DC boost converter with MPPT system. The maximum power point tracking control is based on adaptive fuzzy logic to control ON/OFF time of IGBT switch of DC-DC boost converter. The proposed DC to DC converter is designed by using the Multisim software while the controller programme will be carried out by using the Matlab Simulink software. Pulse width modulation will be generated by the controller to trigger the IGBT gate. The performance of the proposed model is evaluated by the simulation and the result show that our proposed converter can convert more power from generated voltage. By using the fuzzy logic method to track the maximum power of the PV array, it is faster and the voltage is stable.

scholarly journals Evaluation of Fuzzy Logic Subsets Effects on Maximum Power Point Tracking for Photovoltaic System

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Shahrooz Hajighorbani ◽  
M. A. M. Radzi ◽  
M. Z. A. Ab Kadir ◽  
S. Shafie ◽  
Razieh Khanaki ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Climate Conditions ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Photovoltaic system (PV) has nonlinear characteristics which are affected by changing the climate conditions and, in these characteristics, there is an operating point in which the maximum available power of PV is obtained. Fuzzy logic controller (FLC) is the artificial intelligent based maximum power point tracking (MPPT) method for obtaining the maximum power point (MPP). In this method, defining the logical rule and specific range of membership function has the significant effect on achieving the best and desirable results. This paper presents a detailed comparative survey of five general and main fuzzy logic subsets used for FLC technique in DC-DC boost converter. These rules and specific range of membership functions are implemented in the same system and the best fuzzy subset is obtained from the simulation results carried out in MATLAB. The proposed subset is able to track the maximum power point in minimum time with small oscillations and the highest system efficiency (95.7%). This investigation provides valuable results for all users who want to implement the reliable fuzzy logic subset for their works.

scholarly journals VHDL Based Maximum Power Point Tracking of Photovoltaic Using Fuzzy Logic Control

2017 ◽  
Vol 7 (6) ◽  
pp. 3454 ◽  
Author(s):  
Doaa M. Atia ◽  
Hanaa T. El-madany
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Matlab Simulink ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Simulation Results ◽  
Power Point

It is important to have an efficient maximum power point tracking (MPPT) technique to increase the<em> </em>photovoltaic (PV) generation system output efficiency. This paper presents a design of MPPT techniques for<em> </em>PV module to increase its efficiency. Perturb and Observe method (P&amp;O), incremental conductance method (IC), and Fuzzy logic controller (FLC) techniques are designed to be used for MPPT. Also FLC is built using<em> </em>MATLAB/ SIMULINK and compared with the FLC toolbox existed in the MATLAB library. FLC does not<em> </em>need knowledge of the exact model of the system so it is easy to implement. A comparison between different<em> </em>techniques shows the effectiveness of the fuzzy logic controller techniques.  Finally, the proposed FLC is<em> </em>built in very high speed integrated circuit description language (VHDL). The simulation results obtained with<em> </em>ISE Design Suite 14.6 software show a satisfactory performance with a good agreement compared to obtained values from MATLAB/SIMULINK. The good tracking efficiency and rapid response to environmental parameters changes are adopted by the simulation results.

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