scholarly journals Integral Backstepping Control for Maximum Power Point Tracking and Unity Power Factor of a Three Phase Grid Connected Photovoltaic System

Author(s):  
Hicham Bahri ◽  
Mohamed Aboulfatah ◽  
M’hammed Guisser ◽  
Elhassane Abdelmounim ◽  
Mohammed El Malah

This paper presents a robust control strategy for a grid connected photovoltaic system with a boost converter by using an integral Backstepping method based on a nonlinear state model, which guarantees the Lyapunov stability of the global system. The system has tracked precisely the maximum power point, with a very fast response and the unit power factor has been observed under different atmospheric conditions. Moreover, the best advantage of the controller is that it’s a good corrector of the grid perturbation and system parameter disturbance. The simulation result has demonstrated the performance of this strategy.

Designs ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 51
Author(s):  
Mahdi Shahparasti ◽  
Mehdi Savaghebi ◽  
Ebrahim Adabi ◽  
Thomas Ebel

This paper aims to present a new structure of the parallel Z-source inverters (ZSIs) for dual-input single-phase grid-connected photovoltaic (PV) systems. The ZSI is a single-stage buck-boost converter that uses an inductor-capacitor network between the inverter bridge and the PV string and follows the maximum power point by applying the shoot-through vector. Therefore, a DC/DC converter is no longer needed to track the maximum power point, and the cost and complexity of the power conditioning system (PCS) are reduced. For controlling the proposed PCS, a cascade control structure is employed in this paper. The inner current loop injects the maximum active power with unity power factor sinusoidal current to the grid. The outer capacitor voltage loop is applied to control capacitors voltages in the Z-source networks. Additionally, an enhanced dual-string maximum power point tracking (eDS-MPPT) method is proposed to find MPPs with minimum burden competitional. The eDS-MPPT does not need the PVs voltages measurements compared to other MPPT methods. The simulation results confirm the accuracy of the performance of the system.


2019 ◽  
Vol 142 (1) ◽  
Author(s):  
Hafsa Abouadane ◽  
Abderrahim Fakkar ◽  
Benyounes Oukarfi

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.


Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3260
Author(s):  
Ming-Fa Tsai ◽  
Chung-Shi Tseng ◽  
Kuo-Tung Hung ◽  
Shih-Hua Lin

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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