Comparative study of P&amp;O and INC MPPT algorithms for DC-DC Converter Based PV System on MATLAB/SIMULINK

Lemmassi, Assiya; Derouich, Aziz; Hanafi, Ahmed

doi:10.1109/icecocs50124.2020.9314498

Cited by 12 publications

(5 citation statements)

References 6 publications

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“…Additionally, the MPP of a PV module on the voltagecurrent (U-I) and voltage-power (U-P) characteristics should also be determined and updated to ensure that the PV module is always operated adaptively and optimally under various operational conditions. There are currently many techniques applied to determine MPPs of the PV modules such as PO algorithms [34], [35] and InC algorithms [36], [37]. Several previous studies show that the PO algorithm exhibits disadvantages such as oscillations around the MPP in steadystate conditions, deviations from the MPP in quickly changing conditions of the irradiance and temperature and requirements of an appropriate perturbation step size [38].…”

Section: Siaw-pso Algorithmmentioning

confidence: 99%

Estimation for Model Parameters and Maximum Power Points of Photovoltaic Modules Using Stochastic Fractal Search Algorithms

2022

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The performance of a photovoltaic (PV) power generation system could be improved through the optimal control and operation of a PV module which is one of the fundamental components of this system. Thus, an appropriate PV module model along with precise knowledge of its parameters is necessary. This paper proposes a novel technique to estimate the source current, the saturation current of diodes, the shunt resistance, the series resistance, the ideality coefficient of diodes and the maximum power points (MPPs) of PV modules at the same time. This estimation problem can be described by the minimization of the root mean squared error (RMSE) of the powers obtained from the PV module through estimation and experiment. The improved stochastic fractal search (ISFS) algorithm is proposed to solve this minimization with two modifications. The first replaces the logarithmic function with the exponential function in the standard deviation of the diffusion technique to improve the exploration ability efficiently in the search space. The second utilizes the sine map instead of the uniform distribution in both the diffusion and update techniques for improving the performance of the ISFS algorithm. Numerical results demonstrate the remarkable ability of the ISFS algorithm in obtaining both the model parameters and MPPs of the PV module with high accuracy. The comparison shows that the ISFS algorithm outperforms other meta-heuristic algorithms such as a stochastic fractal search (SFS) algorithm, a particle swarm optimization (PSO) algorithm, and an improved particle swarm optimization (IPSO) algorithm in the proposed parameter estimation application.INDEX TERMS Estimation, maximum power point, meta-heuristic algorithms, model parameter, photovoltaic modules

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Section: Siaw-pso Algorithmmentioning

confidence: 99%

Estimation for Model Parameters and Maximum Power Points of Photovoltaic Modules Using Stochastic Fractal Search Algorithms

2022

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“…A photovoltaic module [35], a DC-DC BOOST converter [28][29][30][31][32][33][34][35], an MPPT controller [35], and a load make up a PV system [35][36][37]. The PVS system is depicted in diagram form in Figure 1.…”

Section: System Descriptionmentioning

confidence: 99%

“…Figure 3, displays the electrical circuit of a boost converter [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]: This type of converter can be used as an adapter Sourceload when the load needs a higher voltage than that of the photovoltaic system generator [9-31-39]. Through changing the duty cycle D, it is possible to adapt the source to the load [16].…”

Section: Dc/dc Converter [39]mentioning

confidence: 99%

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Improved Artificial Neural Network Design for MPPT Grid-Connected Photovoltaic Systems

Maarouf

Ksentini

Azzag

et al. 2022

The Scientific Bulletin of Electrical Engineering Faculty

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Photovoltaic (PVS) generators’ nonlinear electrical characteristics allow for greater performance and efficiency when they are forced to operate at their peak power (MPP). This article suggests an adaptive method for maximizing power point tracking that makes use of artificial neural network (ANN) techniques (MPPT). A step-up converter powered by a separate solar generator is under the control of an ANN controller built on a neural network training database (PVS). The results show that ANN-MPPT has good control performance and is near to the maximum power point of PVS when compared to conventional MPPT methods like perturb and observe and incremental conductance.

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“…Under the environmental concern like shortage of energy and pollution, RES such as Solar and Wind are the most suitable replaced energy sources which are presence the foremost energy of recent power systems. Micro grid (MG) integrates flexible DGs, such as wind power, solar power and fuel cells, with manageable storage and loads to form a low-voltage distribution system [3][4][5][6]. They improve the reliability of the network and provide durability and quality electrical energy.…”

Section: Introductionmentioning

confidence: 99%

Cascaded Feed Forward Multilayer Neural Network based MPPT Controller for Improving the Performance of Photovoltaic System

Rupesh¹

2021

TURCOMAT

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This paper deals with the energy production of photovoltaic (PV) cells in different weather conditions. Today, photovoltaic generation plays an important role in generating electricity and satisfies the demand of the island's consumers. The power generation of the PV cell was completely dependent upon sunlight and temperature, but sunlight and temperature changed forever in nature. The many researchers are working on different MPPT technologies for a PV system. Conventional MPPT controllers cannot withstand a sudden change of weather conditions. The main aim of this article is to compare the various conventional and intelligent controller such as the GA, Fuzzy, KGMO, and CNFF for MPPT of the PV system. The proposed intelligent controller was developed and simulated by the MATLAB environment for MPPT in the PV system. In addition, the above results are evaluated and compared. Based on performance, the optimal smart controller has been recommended as MPPT of the PV system

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Comparative study of P&O and INC MPPT algorithms for DC-DC Converter Based PV System on MATLAB/SIMULINK

Cited by 12 publications

References 6 publications

Estimation for Model Parameters and Maximum Power Points of Photovoltaic Modules Using Stochastic Fractal Search Algorithms

Estimation for Model Parameters and Maximum Power Points of Photovoltaic Modules Using Stochastic Fractal Search Algorithms

Improved Artificial Neural Network Design for MPPT Grid-Connected Photovoltaic Systems

Cascaded Feed Forward Multilayer Neural Network based MPPT Controller for Improving the Performance of Photovoltaic System

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