scholarly journals Perturb and Observe Algorithm in Maximum Power Point Tracking (MPPT) for Solar Generation

2020 ◽  
Vol 9 (4) ◽  
pp. 547-549
Keyword(s):  
Operating Cost ◽  
Photovoltaic Cells ◽  
Electrical Energy ◽  
Power Source ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point ◽  
Sustainable Power

The photovoltaic system is one of the promising sustainable power source advancements. In spite of the fact that the energy conversion productivity of the framework is still low, it has the preferred position that the operating cost is free. MPPTMaximum power point tracking is a critical part of photovoltaic frameworks. Solar energy based vitality is viewed as one of the significant sources of sustainable power source, accessible in abundance and furthermore free of cost. Solar based photovoltaic cells are utilized to change over solar-based energy into unregulated electrical energy. These solar oriented photovoltaic cells show nonlinear qualities and give low productivity. In this method, it gets basic to extricate maximum power from solar oriented photovoltaic cells utilizing MPPT. This paper proposes P&O algorithm for refining the proficiency of the single-stage grid-associated power conversion framework. Further, this paper recommends a coordinated controller that is utilized to progress the nature of the power supply to the grid.

scholarly journals An improved control for MPPT based on FL-PSo to minimize oscillation in photovoltaic system

2020 ◽  
Vol 11 (2) ◽  
pp. 1082 ◽  
Author(s):  
Aji Akbar Firdaus ◽  
Riky Tri Yunardi ◽  
Eva Inaiyah Agustin ◽  
Sisca D. N. Nahdliyah ◽  
Teguh Aryo Nugroho
Keyword(s):  
Output Power ◽  
Weather Conditions ◽  
Electrical Energy ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point ◽  
Time Required

Photovoltaic (PV) is a source of electrical energy derived from solar energy and has a poor level of efficiency. This efficiency is influenced by PV condition, weather, and equipments like Maximum Power Point Tracking (MPPT). MPPT control is widely used to improve PV efficiency because MPPT can produce optimal power in various weather conditions. In this paper, MPPT control is performed using the Fuzzy Logic-Particle Swarm Optimization (FL-PSO) method. This FL-PSO is used to get the Maximum Power Point (MPP) and minimize the output power oscillation from PV. From the simulation results using FL-PSO, the values of voltage, and output power from the boost converter are 183.6 V, and 637.7 W, respectively. The ripple of output power from PV with FL-PSO is 69.5 W. Then, the time required by FL-PSO reaches MPP is 0.354 s. Compared with MPPT control based on the PSO method, the MPPT technique using FL-PSO indicates better performance and faster than the PSO.

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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