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

2013 ◽  
Vol 23 (2) ◽  
pp. 145-167 ◽  
Author(s):  
Nadia Drir ◽  
Linda Barazane ◽  
Malik Loudini
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Fast Response ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Precise Control ◽  
Power Point

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.

scholarly journals Optimization of a Grid Connected Photovoltaic System using Fuzzy Logic Control

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Dikio C. Idoniboyeobu ◽  
Sunny Orike ◽  
Peace B. Biragbara
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Maximum Power ◽  
The Other ◽  
Photovoltaic System ◽  
Renewable Energy Resources ◽  
Maximum Power Point ◽  
Power Point ◽  
Continuous Power

Solar Photovoltaic energy generating system is one of the auspicious renewable energy resources that use the ample energy from the sun with clean, inexhaustible and environment friendly cyclic operations. However, the intermittent nature of the output power of PV systems reduces their reliability in delivering continuous power to customers. In this work, we propose an efficient and precise technique using a fuzzy controller and simulated in MATLAB environment, for tracking maximum power point in PV system. The fuzzy Logic model results were compared with other methods such as Perturb and Observe (P&O) and Proportional Integral Differential (PID) for validation. The results show that the Fuzzy Logic Controller, an Artificial Intelligence technique under various conditions was able to track the peak power point under lesser time - it took the fuzzy model less than 0.4 secs to attain maximum power while the other controllers took more than 0.7 and 0.8 seconds respectively. It was also observed that the fuzzy logic controller showed greater stability when the maximum power point was attained than the other controller. Hence the fuzzy logic controller gave a better overall performance than other conventional controllers.

Maximum Power Point Tracker Using Fuzzy Logic Controller with Reduced Rules

2018 ◽  
Vol 9 (3) ◽  
pp. 1381
Author(s):  
Adel Haddouche ◽  
Mohammed Kara ◽  
Lotfi Farah
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Good Alternative ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Practical Applications ◽  
Performance Improvements ◽  
Point Tracking ◽  
Power Point

<p><span lang="EN-US">This paper presents a fuzzy logic controller for maximum power point tracking (MPPT) in photovoltaic system with reduced number of rules instead of conventional 25 rules to make the system lighter which will improve the tracking speed and reduce the static error, engendering a global performance improvements. in this work the proposed system use the power variation and current variation as inputs to simplify the calculation, the introduced controller is connected to a conventional grid and simulated with MATLAB/SIMULINK. The simulation results shows a promising indication to adopt the introduced controller as an a good alternative  to traditional MPPT system for further practical applications</span></p>

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 A comparative study on conventional and modern maximum power point tracking algorithms applied to photovoltaic systems

2019 ◽  
Vol 9 (2) ◽  
pp. 29-35
Author(s):  
Rachid Belaidi ◽  
Boualem Bendib ◽  
Djamila Ghribi ◽  
Belkacem Bouzidi ◽  
Mohamed Mghezzi Larafi
Keyword(s):  
Fuzzy Logic ◽  
Comparative Study ◽  
Fuzzy Controller ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Pv System ◽  
Software Environment ◽  
Maximum Power Point ◽  
Pv Systems ◽  
Power Point

The main goal of maximum power point (MPP) tracking control is to extract the maximum photovoltaic (PV) power by finding the optimal operating point under varying atmospheric conditions to improve the efficiency of PV systems. In recent years, the field of tracking the MPP of PV systems has attracted the interest of many researchers from the industry and academia. This research paper presents a comparative study between the modern fuzzy logic based controller and the conventional perturb & observe (P&O) technique. The comparative study was carried out under different weather conditions in order to analyse and evaluate the performance of the PV system. The overall system simulation has been performed using Matlab/Simulink software environment. The simulation results show that the dynamic behaviour exhibited by the modern fuzzy controller outperforms that of the conventional controller (P&O) in terms of response time and damping characteristics.   Keywords: MPPT, photovoltaic system, fuzzy logic control, P&O algorithm.

scholarly journals Design and Implementation of Modified INC, Conventional INC, and Fuzzy Logic Controllers Applied to a PV System under Variable Weather Conditions

Designs ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 71
Author(s):  
Maroua Bouksaim ◽  
Mohcin Mekhfioui ◽  
Mohamed Nabil Srifi
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Weather Conditions ◽  
Energy Conversion Efficiency ◽  
Fast Response ◽  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Simulation Results ◽  
Power Point

Maximum power point tracking (MPPT) algorithms are used in photovoltaic applications to extract the maximum power that the photovoltaic (PV) panel can produce, which depends on two inputs that are: temperature and irradiance. A DC-DC converter is inserted between the photovoltaic panel and the load to obtain the desired voltage level on the load side. In this paper, incremental conductance (INC) algorithm, modified INC, and fuzzy logic controller (FLC) are designed and assessed to improve energy conversion efficiency. These algorithms are applied to the control of boost converter for tracking the maximum power point (MPP). The modified INC offers fast response and good performance in terms of oscillations than conventional INC and FLC. The Matlab/Simulink environment is used to analyze, interpret the simulation results, and show the performances of each algorithm; and Proteus-based Arduino environment is used to implement the three methods in order to compare the Matlab simulation results with measurements acquired during implementation that is similar to real experiment.

scholarly journals Design of a Solar MPP Tracker with improved Fuzzy Logic

2019 ◽  
Vol 8 (3) ◽  
pp. 8465-8469
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Control Technique ◽  
Operating Voltage ◽  
Cell Temperature ◽  
Maximum Power Point ◽  
Sampling Process ◽  
Power Point

This article introduces a fresh control technique for monitoring the maximum power point of the standalone photovoltaic system at variable solar cell temperature and insolation. Here, the method uses a fuzzy logic controller which is used to track maximum radiation of solar at all time and both the azimuth and elevation angles of sun. A sampling process is used to measure the PV array power and voltage that decides an optimal increment of sample which is required to get the optimal operating voltage that permits maximum power tracking. This method provides high accuracy and reliable result around the optimum point. This proposed fuzzy logic based MPP tracker has shown a better performance compare to existing methods with a power conversion efficiency of ~95.7%. Different steps of designed controller and the set of fuzzy logic has been shown along with its simulation

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