scholarly journals Real-time monitoring and diagnosis of photovoltaic system degradation only using maximum power point-the Suns-Vmp method

2018 ◽  
Vol 27 (1) ◽  
pp. 55-66 ◽  
Author(s):  
Xingshu Sun ◽  
Raghu Vamsi Krishna Chavali ◽  
Muhammad Ashraful Alam
Keyword(s):  
Real Time ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Real Time Monitoring ◽  
Maximum Power Point ◽  
Monitoring And Diagnosis ◽  
Power Point

scholarly journals DSPACE Real-Time Implementation of MPPT-Based FLC Method

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Abdullah M. Noman ◽  
Khaled E. Addoweesh ◽  
Hussein M. Mashaly
Keyword(s):  
Real Time ◽  
Fuzzy Logic Controller ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Solar Module ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Maximum power point trackers are so important in photovoltaic systems to improve their overall efficiency. This paper presents a photovoltaic system with maximum power point tracking facility. An intelligent fuzzy logic controller method is proposed in this paper to achieve the maximum power point tracking of PV modules. The system consists of a photovoltaic solar module connected to a DC-DC buck-boost converter. The system is modeled using MATLAB/SIMULINK. The system has been experienced under disturbance in the photovoltaic temperature and irradiation levels. The simulation results show that the proposed maximum power tracker tracks the maximum power accurately and successfully in all conditions tested. The MPPT system is then experimentally implemented. DSPACE is used in the implementation of the MPPT hardware setup for real-time control. Data acquisition and control system is implemented using dSPACE 1104 software and digital signal processor card. The simulation and practical results show that the proposed system tracked the maximum power accurately and successfully under all atmospheric conditions.

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.

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