Adaptive fuzzy controller based MPPT for photovoltaic systems

Guenounou, Ouahib; Dahhou, B.; Chabour, Ferhat

doi:10.1016/j.enconman.2013.07.093

Cited by 158 publications

(55 citation statements)

References 11 publications

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“…For better performance, particularly in reducing steady state power oscillations, Incremental Conductance (InC) method is preferred [21]. In addition, more complex and computationally heavy algorithms such as Neural-Network (NN) and Fuzzy controllers have also been introduced [22], [27]. Even though these methods promise more accurate and reliable results, their complexity and long iterations make them not practical for low cost applications.…”

Section: B Mppt and Reduced Sensor Mpptmentioning

confidence: 99%

Single Sensor Charging System with MPPT Capability for Standalone Streetlight Applications

Osman¹,

Rahim²,

Selvaraj³

et al. 2015

Journal of Power Electronics

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Maximum power point tracking (MPPT) and battery charging control are two important functions for a solar battery charger. The former improves utilization of the available solar energy, while the latter ensures a prolonged battery life. Nevertheless, complete implementation of both functions can be complex and costly, especially for low voltage application such as standalone street lamps. In this paper, the operation of a solar battery charger for standalone street light systems is investigated. Using only one voltage sensor, the solar charger is able to operate in both MPPT and constant voltage (CV) charging mode, hence providing high performance at a low cost. Using a lab prototype and a solar simulator, the operation of the charger system is demonstrated and its performance under varying irradiance is validated.

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Section: B Mppt and Reduced Sensor Mpptmentioning

confidence: 99%

Single Sensor Charging System with MPPT Capability for Standalone Streetlight Applications

Osman¹,

Rahim²,

Selvaraj³

et al. 2015

Journal of Power Electronics

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show abstract

“…Other strategies based on artificial intelligence such as neural networks and genetic algorithms have developed. These methods suffer from oscillation of the operating point around the MPP which leading to significant energy losses especially in large scale photovoltaic systems [4]. In this paper an adaptive fuzzy proportional integral derivative control based maximum power point tracking strategy for photovoltaic system is proposed to maximize the power output of PV generator and to enhance the system performance.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fuzzy Proportional Integral Derivative Controller Based Maximum Power Point Tracking For Photovoltaic System

BOUZI¹

2015

IJIRSET

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ABSTRACT:Due to nonlinear P-V characteristics of photovoltaic generator, a maximum power point tracking(MPPT) algorithm is needed to optimize the performance of photovoltaic (PV) system.In this paper, an adaptive fuzzy proportional integral derivative (AFPID) control based maximum power point tracking strategy for photovoltaic system is proposed. The proposed adaptive fuzzy PID method integrates two level control system architecture, which combines the advantages of conventional PID and fuzzy logic control. Simulation results show that the designed controller guarantees convergence to the maximum power point under different climatic conditions and provides robust responses in rapid variation of load. Compared with the conventional perturb and observe (P&O) approach the proposed AFPID controller can simultaneously improve the dynamic and steady state performance of the PV system.

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“…This method gives fast tracking speed during varying atmospheric conditions. Some methods are based on neural networks and fuzzy logic [3,11,15,16]. The mean advantage is their ability to take into account the nonlinearities without handling nonlinear mathematical models.…”

Section: Introductionmentioning

confidence: 99%

Accurate Maximum Power Point Tracking Algorithm Based on a Photovoltaic Device Model

Bahir

Hassboun

2017

International Journal of Photoenergy

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An accurate method is proposed to track the maximum power point of a photovoltaic module. The method is based on the analytical value of the maximum power point voltage, determined from a mathematical model of the photovoltaic panel. The method has the advantage of accuracy without any oscillations, as with certain conventional methods. The algorithm has also the ability to track accurately the maximum power point under variable atmospheric conditions and load changes. Experimental results are presented to show the effectiveness of the method. The implementation of the method needs an online measurement of irradiance, panel temperature, and panel current and voltage.

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Adaptive fuzzy controller based MPPT for photovoltaic systems

Cited by 158 publications

References 11 publications

Single Sensor Charging System with MPPT Capability for Standalone Streetlight Applications

Single Sensor Charging System with MPPT Capability for Standalone Streetlight Applications

Adaptive Fuzzy Proportional Integral Derivative Controller Based Maximum Power Point Tracking For Photovoltaic System

Accurate Maximum Power Point Tracking Algorithm Based on a Photovoltaic Device Model

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