Maximum power point tracking in grid connected PV system using a novel fuzzy logic controller

Subiyanto, Subiyanto; Mohamed, Azah; Hannan, M. A.

doi:10.1109/scored.2009.5443002

Cited by 29 publications

(18 citation statements)

References 6 publications

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“…This behaviour makes MPP inconstantly tracking the maximum output power of PV generation and leads to unstable power generation. Hence, the process is commonly performed by an advance MPPT algorithm that have been developed previously [10].…”

Section: Solar Panelmentioning

confidence: 99%

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An Intelligent Maximum Power Point Tracking Algorithm for Photovoltaic System

Iman

Roslan

Ker³

et al. 2018

IJET

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This work comprehensively demonstrates the performance analysis of Fuzzy Logic Controller (FLC) with Particle Swarm Optimization (PSO) Maximum Power Point Tracker (MPPT) algorithm on a stand-alone Photovoltaic (PV) applications systems. A PV panel, DC-DC Boost converter and resistive load was utilized as PV system. Three different MPPT algorithms were implemented in the converter. The result obtained from the converter was analyzed and compared to find the best algorithm to be used to identify the point in which maximum power can be achieve in a PV system. The objective is to reduce the time taken for the tracking of maximum power point of PV application system and minimize output power oscillation. The simulation was done by using MATLAB/Simulink with DC-DC Boost converter. The result shows that FLC method with PSO has achieved the fastest response time to track MPP and provide minimum oscillation compared to conventional P&O and FLC techniques.

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Section: Solar Panelmentioning

confidence: 99%

“…To increase the efficiency of solar cell, the method called MPPT is undertaken to match the sources and load properly. Hence, Perturb & Observe (P&O) are popular methods to implement the MPPT [3][4] [10]. It perturbs the operating voltage of PV arrays, and observe the effect of this changes on PV generated power.…”

Section: Mppt With Perturb and Observementioning

confidence: 99%

An Intelligent Maximum Power Point Tracking Algorithm for Photovoltaic System

Iman

Roslan

Ker³

et al. 2018

IJET

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“…Five fuzzy levels are used for all the inputs and outputs variables: NB (negative big), NS (negative small), ZE (zero), PS (positive small), and PB (positive big). References [17,19,21] designed seven fuzzy levels to improve the control surface and to allow a smooth transition from transient to steady state. The user has the flexibility of choosing values of numerical variables of the inputs.…”

Section: E Fuzzy Logic Controllermentioning

confidence: 99%

“…References [18][19][20] compared the results of fuzzy logic controller and P&O controller. It shows that FLC exhibits a better behavior than P&O method, which provides faster tracking of MPP and it presents smoother signal with less fluctuation in steady-state.…”

Section: E Fuzzy Logic Controllermentioning

confidence: 99%

A study of maximum power point tracking algorithms for stand-alone Photovoltaic Systems

Ngan

Tan

2011

2011 IEEE Applied Power Electronics Colloquium (IAPEC)

105

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The Photovoltaic (PV) energy is one of the renewable energies that attracts attention of researchers in the recent decades. Since the conversion efficiency of PV arrays is very low, it requires maximum power point tracking (MPPT) control techniques to extract the maximum available power from PV arrays. In this paper, two categories of MPPT algorithms, namely indirect and direct methods are discussed. In addition to that, the advantages and disadvantages of each MPPT algorithm are reviewed. Simulations of PV modules were also performed using Perturb and Observe algorithm and Fuzzy Logic controller. The simulation results produced by the two algorithms are compared with the expected results generated by Solarex MSX60 PV modules. Besides that, the P-V characteristics of PV arrays under partial shaded conditions are discussed in the last section.

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“…Recently, due to its development and cost reduction, PV systems become an efficient solution to the environment problem [4]. However, the development for improving the efficiency of the PV system is still a challenging field of research [5].…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Perturb & Observe and Fuzzy-Logic Based MPPT Methods for Uniform Environment Conditions

Kandemir

Çetin

Börekçi

2017

PEN

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The power generation from photovoltaic (PV) system is not constant and it varies based on solar irradiance and temperature. For any environmental condition, to convert maximum available solar energy, PV systems must be operated at maximum power point. To accomplish that two different maximum power point tracking (MPPT) methods have been presented in this study. The first method can determine MPP point by measuring the derivative of PV cell power (dP) and PV cell voltage (dV) which is called Perturb & Observe (P&O) method. The second method uses fuzzy-logic-control (FLC) based MPPT method to determine MPP point for actual environment conditions. In this paper, 3kW PV system model is studied in MATLAB. According to the simulated results, FLC based MPPT method has better performance than P&O method. Compared to the P&O method, FLC-based MPPT can increase tracking accuracy and efficiency performance 0.13% under standard test conditions (STC).

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Maximum power point tracking in grid connected PV system using a novel fuzzy logic controller

Cited by 29 publications

References 6 publications

An Intelligent Maximum Power Point Tracking Algorithm for Photovoltaic System

An Intelligent Maximum Power Point Tracking Algorithm for Photovoltaic System

A study of maximum power point tracking algorithms for stand-alone Photovoltaic Systems

A Comparison of Perturb & Observe and Fuzzy-Logic Based MPPT Methods for Uniform Environment Conditions

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