Maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic system

Patcharaprakiti, Nopporn; Premrudeepreechacharn, S.; Sriuthaisiriwong, Yosanai

doi:10.1016/j.renene.2004.11.018

Cited by 168 publications

(25 citation statements)

References 14 publications

(10 reference statements)

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“…Fuzzy controller is designed in such a way that input variable E has to be always zero, which is the condition of MPP. [65][66][67][68][69][70][71][72][73][74] DD. Artificial Neural Network (ANN) based method ANN is a soft computing (SC) technique inspired by central nervous system (brain) and these computational models are capable of machine learning and they are represented as the interconnected neurons (artificial nodes) to form a network similar to biological neural network.…”

Section: Fuzzy Logic Control Methodsmentioning

confidence: 99%

Comprehensive analysis of maximum power point tracking techniques in solar photovoltaic systems under uniform insolation and partial shaded condition

Verma

Nema

Shandilya

et al. 2015

Journal of Renewable and Sustainable Energy

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Power quality assessment of a solar photovoltaic two-stage grid connected system: Using fuzzy and proportional integral controlled dynamic voltage restorer approach J. Renewable Sustainable Energy 7, 013113 (2015); 10.1063/1.4906980Modeling and global maximum power point tracking for photovoltaic system under partial shading conditions using modified particle swarm optimization algorithm J. Renewable Sustainable Energy 6, 063117 (2014); 10.1063/1.4904436Maximum power point tracking of partial shaded photovoltaic array using an evolutionary algorithm: A particle swarm optimization technique J. Renewable Sustainable Energy 6, 023102 (2014); 10.1063/1.4868025Conventional and global maximum power point tracking techniques in photovoltaic applications: A review

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Section: Fuzzy Logic Control Methodsmentioning

confidence: 99%

Comprehensive analysis of maximum power point tracking techniques in solar photovoltaic systems under uniform insolation and partial shaded condition

Verma

Nema

Shandilya

et al. 2015

Journal of Renewable and Sustainable Energy

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“…The input E(k) shows if the load operation point at the instant k is located on the left or on the right of the maximum power point on the PV characteristic, while the input CE(k ) expresses the moving direction of this point. The fuzzy inference is carried out by using Madmani's method, (Table 1), and the defuzzification uses the centre of gravity to compute the output of this FLC which is the duty cycle [3,4]:…”

Section: V-fuzzy Logic Mppt Controllermentioning

confidence: 99%

Modeling and control of a gird connected PV generation system

Bouchafaa¹,

Beriber²,

Boucherit³

2010

18th Mediterranean Conference on Control and Automation, MED'10

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Abstracts-This paper presents the analysis, modelling and control model of the electric part of a grid connected photovoltaic generation system. The model contains a detailed representation of the main components of the system that are the solar array, and the grid side multilevel neutral point clamped (NPC) voltage source inverter (VSI). In order to extract the maximum amount of from the photovoltaic generator, we propose an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and insulation conditions. This method uses a fuzzy logic controller. As part of our work, we will focus on voltage inverter at three levels to NPC structure. The latter can increase the voltage supplied to the load (network) through their topology. Thus, they can generate more voltage sinusoidal possible and improve the total harmonic distortion through the high voltage levels provided by the structure of this new converter. The grid interface inverter transfers the energy drawn from the PV module into the grid by keeping common dc voltage constant. The PQ control approach (Direct Power Control) has been presented for the multilevel inverter. The simulation results under Matlab/Simulink show the control performance and dynamic behaviour of grid connected photovoltaic system. 978-1-4244-8092-0/10/$26.00 ©2010 IEEE

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“…It is important to find the optimal operating voltage (or current) of PV arrays in order to increase the efficiency of PV generators. To achieve this goal, various MPPT algorithms were proposed such as, perturb and observe (P&O) or hill climbing , incremental conductance , voltage‐based (VMPPT) and current‐based (CMPPT) methods, and as well, intelligent computing method . However, all the former MPPT schemes are not suitable for extracting the true maximum power under partial shading conditions.…”

Section: Introductionmentioning

confidence: 99%

A PSO‐based maximum power point tracking for photovoltaic systems under environmental and partially shaded conditions

Sarvi

Ahmadi

Abdi

2013

Progress in Photovoltaics

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To increase the efficiency of photovoltaic (PV) systems, maximum power point (MPP) tracking of the solar arrays is needed. Solar arrays output power depends on the solar irradiance and temperature. Also the mismatch phenomenon caused by partial shade will affect the output power of solar systems and lead to the incorrect operation of conventional MPP tracker. Under partially shaded conditions, the solar array power–current characteristic has multiple maximum. This paper presents a maximum power point tracking (MPPT) with particle swarm optimization method for PV systems under partially shaded condition. The performance of the proposed method is compared with perturb and observe (P&O), improved P&O, voltage‐based maximum power point tracking and current‐based maximum power point tracking algorithms, especially, under partially shaded condition. Simulation results confirm that proposed MPPT algorithm with high accuracy can track the peak power point under different insolation, temperature and partially shaded conditions, and it has the best performance in comparison with four mentioned MPPT algorithms. Also under rapidly changing atmospheric conditions, the P&O algorithm is diverged. Copyright © 2013 John Wiley & Sons, Ltd.

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Maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic system

Cited by 168 publications

References 14 publications

Comprehensive analysis of maximum power point tracking techniques in solar photovoltaic systems under uniform insolation and partial shaded condition

Comprehensive analysis of maximum power point tracking techniques in solar photovoltaic systems under uniform insolation and partial shaded condition

Modeling and control of a gird connected PV generation system

A PSO‐based maximum power point tracking for photovoltaic systems under environmental and partially shaded conditions

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