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

Maarouf, Saliha; Ksentini, Abdelhamid; Azzag, El Bahi; Kebbache, Rachida; Boukerche, Ghania

doi:10.2478/sbeef-2022-0016

The Scientific Bulletin of Electrical Engineering Faculty

2022

DOI: 10.2478/sbeef-2022-0016

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

Saliha Maarouf

Abdelhamid Ksentini

El Bahi Azzag

et al.

Abstract: 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 contro… Show more

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Cited by 3 publications

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Comparative Study Of Five Mppt Controls In Two-Stage Three-Phase Grid-Connected Photovoltaic Systems Under Partial Shading Conditions

Maarouf,

Ksentini,

Azzag

2023

The Scientific Bulletin of Electrical Engineering Faculty

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One of the maximum popular renewable electricity assets is photovoltaics. Grid-connected photovoltaic structures are designed to generate as a lot strength as possible. Photovoltaic systems have nonlinear traits imposed with the aid of environmental factors consisting of radiation and temperature, making it hard to operate at the most power factor. It may additionally be tough to extract the maximum amount of electricity due to the formation of nearby maxima because of other factors which include shading or degradation. There are several MPPT algorithms and approaches that may be used for this. Publications with comparative analyses have also been released. However, in most of these works, comparisons are based on simulations or literature review. From the simplest to the most complex MPPT methods, empirical validation remains important. The two simplest and most widely used MPPT techniques are the perturbation, open-loop, and incremental conductance algorithms. The three most challenging ones are sliding mode control, backstepping controller, and particle swarm optimization. Therefore, five MPPT algorithms are empirically studied in this paper. Under test settings, Matlab/Simulink was used to conduct experimental experiments. The findings demonstrate that under ordinary operating circumstances, the backstepping algorithm is the only one capable of finding the global MPP under the influence of local shadowing.

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Comparative Study Of Five Mppt Controls In Two-Stage Three-Phase Grid-Connected Photovoltaic Systems Under Partial Shading Conditions

Maarouf,

Ksentini,

Azzag

2023

The Scientific Bulletin of Electrical Engineering Faculty

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Etude and Optimization of MPPT Controllers in Photovoltaic Systems with Battery Energy Storage

Ghania,

Amar,

Hichem

2023

The Scientific Bulletin of Electrical Engineering Faculty

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Three different types of MPPT techniques will be studied and compared in this work. MPPT is a technology for maximizing the power produced by solar energy systems. Fuzzy logic-based control (FLC), one of the most widely utilized MPPT approaches, is examined, perturbation and monitoring (P&O), and plug-in (Inc). The power and effectiveness of a solar energy system with lead-acid batteries for storage, an energy management plan, and associated photovoltaics In order to confirm the benefit, FL-MPPT was examined in this study, and the performance of its algorithm was compared and evaluated. Using both techniques, P&O and Inc. Using Matlab/Simulink 2018-a tools, simulation results showed that the power quality was higher using MPPTFLC.

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Enhancing Performance of Photovoltaic Pump Systems in Remote Areas Using a Sliding Mode Technique for Maximum Power Point Tracking

Mahmood

2024

PIER B

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Photovoltaic (PV) systems represent an extremely intriguing alternative in order to provide dry and semi-arid regions in remote locations with water. In this case, a maximum power point tracking (MPPT) unit that aims to regulate the PV panel connected converter duty cycle is necessary to ensure that it operates as efficiently as possible under various operating situations. This study introduces a sliding mode technique-based MPPT control unit with the goal of enhancing photovoltaic pump (PVP) system performance. It discusses this for a number of scenarios, including the presence or absence of batteries, operation under various radiation conditions, and operation in consideration of constant speed and variable load torque. The outcomes of the MATLAB simulation demonstrated that the proposed methodology is preferable compared to the incremental conductance method for the various scenarios, and it achieves better efficiency and lower voltage ripples.

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

Cited by 3 publications

References 35 publications

Comparative Study Of Five Mppt Controls In Two-Stage Three-Phase Grid-Connected Photovoltaic Systems Under Partial Shading Conditions

Comparative Study Of Five Mppt Controls In Two-Stage Three-Phase Grid-Connected Photovoltaic Systems Under Partial Shading Conditions

Etude and Optimization of MPPT Controllers in Photovoltaic Systems with Battery Energy Storage

Enhancing Performance of Photovoltaic Pump Systems in Remote Areas Using a Sliding Mode Technique for Maximum Power Point Tracking

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