scholarly journals FPGA Implementation of a Robust MPPT of a Photovoltaic System Using a Fuzzy Logic Controller Based on Incremental and Conductance Algorithm

2019 ◽  
Vol 9 (4) ◽  
pp. 4322-4328 ◽  
Author(s):  
M. Y. Allani ◽  
D. Mezghani ◽  
F. Tadeo ◽  
A. Mami
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Buck Converter ◽  
Photovoltaic System ◽  
Frequency Noise ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Comparison Results ◽  
Power Point

Climate dependence requires robust control of the photovoltaic system. The current paper is divided in two main sections: the first part is dedicated to compare and evaluate the behaviors of three different maximum power point tracking (MPPT) techniques applied to photovoltaic energy systems, which are: incremental and conductance (IC), perturb and observe (P&O) and fuzzy logic controller (FLC) based on incremental and conductance. A model of a photovoltaic generator and DC/DC buck converter with different MPPT techniques is simulated and compared using Matlab/Simulink software. The comparison results show that the fuzzy controller is more effective in terms of response time, power loss and disturbances around the operating point. IC and P&O methods are effective but sensitive to high-frequency noise, less stable and present more oscillations around the PPM. In the second section, the FPGA platform is used to implement the proposed control. The FLC architecture is implemented on an FPGA Spartan 3E using the ISE Design Suite software. Simulation results showed the effectiveness of the proposed fuzzy logic controller.

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 Improving the dynamic performances of an MPPT controller for a Photovoltaic system using fuzzy logic

2021 ◽  
Vol 229 ◽  
pp. 01013
Author(s):  
Hassan Essakhi ◽  
Sadik Farhat ◽  
Mohamed Mediouni ◽  
Yahya Dbaghi
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Controller ◽  
Photovoltaic System ◽  
Pv System ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Perturb And Observe ◽  
Dynamic Performances ◽  
Mppt Controller ◽  
Power Point

This paper deals with analysis, modeling, and simulation of a Photovoltaic (PV) system with an intelligent Maximum Power Point Tracking (MPPT) controller based on fuzzy logic and to compare the dynamic performances: rapidity and stability of a fuzzy controller with the traditional controller based on the “Perturb and Observe” algorithm (P&O). The system is simulated under Simulink/Matlab environment. The simulation results show that the fuzzy MPPT controller is faster and more stable during abrupt changes in irradiation values.

scholarly journals Efficiency improvement of photovolatic by using maximum power point tracking based on a new fuzzy logic controller

2018 ◽  
Vol 9 (2) ◽  
pp. 57
Author(s):  
Machmud Effendy ◽  
Nuralif Mardiyah ◽  
Khusnul Hidayat
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Maximum Power Point Tracking ◽  
Buck Converter ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Fuzzy Algorithm ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Maximum power point tracking (MPPT) is a technique to maximize the power output of photovoltaic (PV). Therefore, to achieve higher PV efficiency, the development of MPPT control algorithm is necessary. Recently, it was revealed that fuzzy logic controller (FLC) is better than other control algorithms and is possible toe developed. This study fabricated and implemented MPPT based on the proposed a new FLC. Input Calculator (IC) via sensors reads current and voltage of PV and generates the comparison of voltage and current of PV, then IC output becomes fuzzy algorithm input. Fuzzy algorithm produces duty cycle that drives synchronous buck converter. The result showed that MPPT system with proposed FLC method has 99.1% efficiency while MPPT system with P&O method has 95.5% efficiency. From the obtained result, it can be concluded that the MPPT based on the proposed FLC can increase the overall efficiency of the system to 99.3%.

scholarly journals Comparison between proposed fuzzy logic and ANFIS for MPPT control for photovoltaic system

2020 ◽  
Vol 11 (2) ◽  
pp. 1065
Author(s):  
Lotfi Farah ◽  
Adel Haddouche ◽  
Ali Haddouche
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Photovoltaic System ◽  
Pv System ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Neuro Fuzzy ◽  
Current Variation ◽  
Power Point

In this paper, a maximum power point tracking (MPPT) algorithm for photovoltaic (PV) systems is achieved based on fuzzy logic controller (FLC) and compared with an anfis (neuro-fuzzy) based mppt controller, this method allies the abilities of artificial neural networks in learning and the power of fuzzy logic to handle imprecise data. Both methods are simulated using matlab/ simulink. The choise of power variation and the current variation as inputs of the proposed controllersreducesthe calculation. Both FLC and ANFIS based MPPTare tested in terms of steady state performance and the pv system dynamic.

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