Improving the Accuracy and Response Time of P&O in Detecting the Maximum Power Point for a Photovoltaic System Environment

2018 ◽  
Author(s):  
Imad Ahmad Elzein ◽  
Yury Petrenko ◽  
Moustapha Kurdi
Keyword(s):  
Response Time ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
System Environment ◽  
Power Point

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 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.

Upon Power Loses due to Current Harmonics in a Fotovoltaic System, Opperating at Maximum Power Point

2013 ◽  
Vol 853 ◽  
pp. 352-357
Author(s):  
Calin Chioreanu
Keyword(s):  
Electronic System ◽  
Pollution Source ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Power Losses ◽  
Maximum Power Point ◽  
Current Harmonics ◽  
Solar Battery ◽  
Harmonic Pollution ◽  
Power Point

Photovoltaic panels (PF), combined with lead-acid battery (AE), are increasingly used, to produce electricity. To work in maximum power points, between (PF) and (AE) is interposed a static converter (DC-DC), which is a harmonic pollution source. Within the paper there are calculated the power losses, due to current harmonics, of a photovoltaic system working at its maximum power. Photovoltaic system works at its maximum power, if in the electronic system there is permanently voltage control among solar battery terminals.

Robust mixed H2/H∞ fuzzy tracking control of photovoltaic system subject to asymmetric actuator saturation

2021 ◽  
pp. 014233122110521
Author(s):  
Noureddine Boubekri ◽  
Sofiane Doudou ◽  
Dounia Saifia ◽  
Mohammed Chadli
Keyword(s):  
Actuator Saturation ◽  
Atmospheric Condition ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Attraction Domain ◽  
Duty Ratio ◽  
Linear Matrix ◽  
Maximum Power Point ◽  
Power Extraction ◽  
Power Point

This paper focuses on mixed [Formula: see text] fuzzy maximum power point tracking (MPPT) of photovoltaic (PV) system under asymmetric saturation and variations in climatic conditions. To maximize the power from the PV panel array, the DC–DC boost converter is controlled by its duty ratio which is practically saturated between 0 and 1. MPPT based on conventional control presents the problems of oscillations around maximum power point (MPP) and divergence under rapid climatic changes. In order to attenuate the effect of atmospheric condition variation and take into account asymmetric saturation of the duty ratio, we propose a novel robust saturated controller based on both [Formula: see text] performances and Takagi-Sugeno (T-S) representation of PV-boost nonlinear system. Within this approach, the nonlinear PV-boost system and its reference are first described by T-S fuzzy models. Second, the saturation effect is represented by a polytopic model. Then, a fuzzy integral state feedback controller is designed to achieve stable MPPT control. Based on Lyapunov function, the mixed [Formula: see text] stabilization conditions are derived in terms of linear matrix inequalities (LMIs). The optimization of the attraction domain of closed-loop system is solved as a convex optimization problem in LMI terms. Finally, the efficiency of the proposed controller under irradiance and temperature variations is demonstrated through the simulation results. The comparison with some existing controllers shows an improvement of MPPT control performance in terms of power extraction.

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