An Optimal Maximum Power Point Tracking Algorithm for PV Systems With Climatic Parameters Estimation

Chikh, A.; Chandra, Ambrish

doi:10.1109/tste.2015.2403845

Cited by 83 publications

(37 citation statements)

References 36 publications

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“…represents the PV module (I-V) curve, which is described by the quadratic interpolation function. The interpolation nodes 1 and 2 represent the voltage values at the two sampling points ( 1 and 2 ), while 0 represents the voltage 0 of the short circuit current, which is equal to zero, and 3 represents the open circuit voltage provided by the PV module data sheet. The function values 1 and 2 correspond to the voltage values, representing the duty cycle ( 1 , 2 ), the values of the sampling points, and 0 and 3 represent the duty cycle ( | and | ) at the points, which are equal to 1 and 0, respectively.…”

Section: Mppt Algorithm Based On Numerical Calculationmentioning

confidence: 99%

“…Several MPPT methods have been developed thus far, ranging from the simple to the more complex, and dependent on the weather conditions and the control strategies used. Among these are the Perturb and Observe (P&O) method [1] and [3] and the Incremental Conductance (IncCond) method [4], [5]. These algorithms have the advantage of working independently, as knowledge of PV generator characteristics is not critical.…”

Section: Introductionmentioning

confidence: 99%

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A Novel MPPT Algorithm Based on Particle Swarm Optimization for Photovoltaic Systems

Koad

Zobaa

El-Shahat

2017

IEEE Trans. Sustain. Energy

287

121

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Abstract-This paper describes a new maximum-power-pointtracking method for a photovoltaic system based on the Lagrange Interpolation Formula and proposes the particle swarm optimization method. The proposed control scheme eliminates the problems of conventional methods by using only a simple numerical calculation to initialize the particles around the global maximum power point. Hence, the suggested scheme will utilize fewer iterations to reach the maximum power point.

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Section: Mppt Algorithm Based On Numerical Calculationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel MPPT Algorithm Based on Particle Swarm Optimization for Photovoltaic Systems

Koad

Zobaa

El-Shahat

2017

IEEE Trans. Sustain. Energy

287

121

View full text Add to dashboard Cite

show abstract

“…(1) and (2) [15][16][17]. In these equations, I ph , I d , I Rsh , K, I 0 , N s , A, q, and T j represent the photo-generated current, diode-current, shunt-leakage current, Boltzmann's constant (J/K), diode reverse bias saturation current, number of PV cells associated in serial, ideality factor of the P-N junction, electron charge (C), and junction temperature of the solar cell, respectively.…”

Section: Modeling and Characterization Of The Pv Generatormentioning

confidence: 99%

Relevance of the P & O MPPT Technique in an Original PV-Powered Water Pumping Application

Aissou¹,

Jacques²,

Mokrani³

et al. 2015

JEPE

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Many papers exploiting the various MPPT (maximum power point tracking) techniques in PV (photovoltaic) applications, from the simple to the most complicated, can be found in literature. However, these techniques may not always be easy to implement in industrial applications. The main challenge of this paper is to model and implement the P & O (perturb and observe) algorithm in a low-cost PV-powered pumping system. To that end, a comparative investigation of the performance characteristics of the most popular MPPT methods, such as FOCV (fractional open circuit voltage), FSCC (fractional short circuit current), FLC (fuzzy logic control), ANN (artificial neural network) and INC (incremental conductance) is presented. This analysis is helpful to highlight the relevance of the P & O technique taking better account of complexity, difficulty of implementation and cost considerations in water pumping applications. The targeted PV-powered pumping system is based on a single-phase induction motor supplied by a three-phase inverter controlled by the DTC (direct torque control) technique. This stand-alone PV system is dedicated to water pumping, especially in rural areas that have no access to national grids but have sufficient amount of solar radiation. Simulation modeling (Matlab/Simulink) and experimental results are presented to demonstrate the relevance of the system.

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“…Fuzzy logic (FL) controllers have been applied to a wide range of applications in various fields. FL has been further developed for power conversion applications, since its operation principle does not require precise knowledge of the load parameters [1,3]. Hence, the estimation of system uncertainties can be accomplished by FL.…”

Section: Introductionmentioning

confidence: 99%

Particle swarm optimization tuned fuzzy terminal sliding mode control for UPS inverters

Chang

et al. 2015

IFS

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Abstract. This paper proposes a particle swarm optimization algorithm tuned fuzzy terminal sliding mode control for the application of UPS inverters. Though classic sliding mode control (SMC) is insensitive to system uncertainties, it possesses an infinite system-state convergence time. For high-accuracy tracking control, a terminal sliding mode control (TSMC) is developed to provide a finite system-state convergence time. However, difficult estimation occurs in TSMC, and incurs high UPS inverter voltage harmonics and slow dynamic response. To obtain high-quality UPS inverter output voltage, a fuzzy logic (FL) with a computationally simple and practically easy estimator is integrated into TSMC to resolve system uncertainties. Simultaneously, the particle swarm optimization (PSO) algorithm is applied to optimally tune the control gains of the TSMC with a fuzzy estimator. Results indicate that the presented combination of PSO, FL and TSMC yields a closed-loop UPS inverter with good performance under various loading conditions. Simulation and experimental results indicate that the proposed control can achieve low total harmonic distortion (THD) under nonlinear loading conditions and fast dynamic response under transient loading conditions.

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An Optimal Maximum Power Point Tracking Algorithm for PV Systems With Climatic Parameters Estimation

Cited by 83 publications

References 36 publications

A Novel MPPT Algorithm Based on Particle Swarm Optimization for Photovoltaic Systems

A Novel MPPT Algorithm Based on Particle Swarm Optimization for Photovoltaic Systems

Relevance of the P & O MPPT Technique in an Original PV-Powered Water Pumping Application

Particle swarm optimization tuned fuzzy terminal sliding mode control for UPS inverters

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