scholarly journals Modeling of photovoltaic system with maximum power point tracking control by neural networks

2019 ◽  
Vol 10 (3) ◽  
pp. 1575
Author(s):  
Farid Saadaoui ◽  
Khaled Mammar ◽  
Abdaldjabar Hazzab
Keyword(s):  
Climatic Conditions ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Photovoltaic Module ◽  
Neuron Network ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point ◽  
And Control

<p>This paper presented the study, development and implementation of the maximum power point of a photovoltaic energy generator adapted by elevator converter and controlled by a maximum power point command. In order to improve photovoltaic system performance and to force the photovoltaic generator to operate at its maximum power point, the idea of the context of this paper deals with the exploitation of the technique of the artificial intelligence mechanism (neural network) certainly based on the three parts of the photovoltaic system (photovoltaic  module inputs (temperature and  solar radiation), photovoltaic module and control (MPPT)) that have been adopted within a simulation time of 24 hours.</p><p>In addition, to reach the optimal operating point regardless of variations in climatic conditions, the use of a neuron network based disturbance and observation algorithm (P&amp;O) is put into service of the system given its reliability, its simplicity and view that at any time it can follow the desired maximum power.</p><p>The entire system is implemented in the Matlab / Simulink environment where simulation results  obtained are very promising and have shown the effectiveness and speed of neural technology that still require a learning base so to improve the performance of photovoltaic systems and exploit them in energy production, as well as this technique has proved that these results are much better in terms (of its very great precision and speed of computation) than those of the controller based on the conventional MPPT method P&amp;O.</p>

Optimal Command for Photovoltaic Systems in Real Outdoor Weather Conditions

2019 ◽  
Vol 142 (1) ◽  
Author(s):  
Hafsa Abouadane ◽  
Abderrahim Fakkar ◽  
Benyounes Oukarfi
Keyword(s):  
Maximum Power Point Tracking ◽  
Accurate Determination ◽  
Weather Conditions ◽  
Climatic Conditions ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

The photovoltaic panel is characterized by a unique point called the maximum power point (MPP) where the panel produces its maximum power. However, this point is highly influenced by the weather conditions and the fluctuation of load which drop the efficiency of the photovoltaic system. Therefore, the insertion of the maximum power point tracking (MPPT) is compulsory to track the maximum power of the panel. The approach adopted in this paper is based on combining the strengths of two maximum power point tracking techniques. As a result, an efficient maximum power point tracking method is obtained. It leads to an accurate determination of the MPP during different situations of climatic conditions and load. To validate the effectiveness of the proposed MPPT method, it has been simulated in matlab/simulink under different conditions.

scholarly journals Simulation of Standalone Three-Phase Photovoltaic System with SPWM and SVPWM Techniques

2020 ◽  
Vol 9 (4) ◽  
pp. 2208-2215
Keyword(s):  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Voltage Source ◽  
Photovoltaic Module ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Three Phase ◽  
Power Point

Maximum power point tracking is a method employed to produce the utmost power available from the photovoltaic module. To date, many algorithms for maximum power point tracking technique had been stated, every with its own capabilities. In this paper, a Luo converter with high-voltage conversion gain is employed to track photovoltaic panels at maximum power and to step up the voltage to a higher level. This work also aims to validate the performance of the maximum power point tracking system with Luo converter which utilizes incremental conductance techniques. Space vector modulation and sinusoidal pulse width modulations are the control techniques employed to control the three-phase voltage source converter. In order to measure the overall performance indices of the proposed system, a simulation is carried out in MATLAB / Simulink environment.

Standalone Photovoltaic System with Maximum Power Point Tracking

2018 ◽  
Vol 7 (3) ◽  
pp. 94-111 ◽  
Author(s):  
Hanane Yatimi ◽  
Elhassan Aroudam
Keyword(s):  
Output Power ◽  
Maximum Power Point Tracking ◽  
Climatic Conditions ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Pv System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

In this article, on the basis of studying the mathematical model of a PV system, a maximum power point tracking (MPPT) technique with variable weather conditions is proposed. The main objective is to make a full utilization of the output power of a PV solar cell operating at the maximum power point (MPP). To achieve this goal, the incremental conductance (IC) MPPT technique is applied to an off-grid PV system under varying climatic conditions, in particular, solar irradiance and temperature that are locally measured in Northern Morocco. The output power behavior and the performance of the system using this technique have been analyzed through computer simulations to illustrate the validity of the designed method under the effect of real working conditions.

scholarly journals A Novel DSP-Based MPPT Control Design for Photovoltaic Systems Using Neural Network Compensator

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3260
Author(s):  
Ming-Fa Tsai ◽  
Chung-Shi Tseng ◽  
Kuo-Tung Hung ◽  
Shih-Hua Lin
Keyword(s):  
Neural Network ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Solar Irradiation ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Irradiation Cell ◽  
Power Point ◽  
Neural Network Compensator

In this study, based on the slope of power versus voltage, a novel maximum-power-point tracking algorithm using a neural network compensator was proposed and implemented on a TI TMS320F28335 digital signal processing chip, which can easily process the input signals conversion and the complex floating-point computation on the neural network of the proposed control scheme. Because the output power of the photovoltaic system is a function of the solar irradiation, cell temperature, and characteristics of the photovoltaic array, the analytic solution for obtaining the maximum power is difficult to obtain due to its complexity, nonlinearity, and uncertainties of parameters. The innovation of this work is to obtain the maximum power of the photovoltaic system using a neural network with the idea of transferring the maximum-power-point tracking problem into a proportional-integral current control problem despite the variation in solar irradiation, cell temperature, and the electrical load characteristics. The current controller parameters are determined via a genetic algorithm for finding the controller parameters by the minimization of a complicatedly nonlinear performance index function. The experimental result shows the output power of the photovoltaic system, which consists of the series connection of two 155-W TYN-155S5 modules, is 267.42 W at certain solar irradiation and ambient temperature. From the simulation and experimental results, the validity of the proposed controller was verified.

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