scholarly journals Integrated energy management converter based on maximum power point tracking for photovoltaic solar system

2022 ◽  
Vol 12 (2) ◽  
pp. 1211
Author(s):  
Mounir Ouremchi ◽  
Said El Mouzouade ◽  
Karim El Khadiri ◽  
Ahmed Tahiri ◽  
Hassan Qjidaa
Keyword(s):  
Power Efficiency ◽  
High Efficiency ◽  
Maximum Power Point Tracking ◽  
Power Converter ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Average Output ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

This paper presents an integrated power control system for photovoltaic systems based on maximum power point tracking (MPPT). The architecture presented in this paper is designed to extract more power from photovoltaic panels under different partial obscuring conditions. To control the MPPT block, the integrated system used the ripple correlation control algorithm (RCC), as well as a high-efficiency synchronous direct current (DC-DC) boost power converter. Using 180 nm complementary metal-oxide-semiconductor (CMOS) technology, the proposed MPPT was designed, simulated, and layout in virtuoso cadence. The system is attached to a two-cell in series that generates a 5.2 V average output voltage, 656.6 mA average output current, and power efficiency of 95%. The final design occupies only 1.68 mm2.

A Comparative Study on Maximum Power Point Tracking Techniques of Photovoltaic Systems

2018 ◽  
Vol 7 (1) ◽  
pp. 66-85 ◽  
Author(s):  
Afef Badis ◽  
Mohamed Habib Boujmil ◽  
Mohamed Nejib Mansouri
Keyword(s):  
High Efficiency ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Conventional Methods ◽  
Power Point

This article concerns maximizing the energy reproduced from the photovoltaic (PV) system, ensured by using an efficient Maximum Power Point Tracking (MPPT) process. The process should be fast, rigorous and simple for implementation because the PV characteristics are extremely affected by fast changing conditions and Partial Shading (PS). PV systems are popularly known to have many peaks (one Global Peak (GP) and several local peaks). Therefore, the MPPT algorithm should be able to accurately detect the unique GP as the maximum power point (MPP), and avoid any other peak to mitigate the effect of (PS). Usually, with no shading, nearly all the conventional methods can easily reach the MPP with high efficiency. Nonetheless, they fail to extract the GP when PS occurs. To overcome this problem, Evolutionary Algorithms (AEs), namely the Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are simulated and compared to the conventional methods (Perturb & Observe) under the same software.

scholarly journals Design and Experimental Implementation of a Hysteresis Algorithm to Optimize the Maximum Power Point Extracted from a Photovoltaic System

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1866 ◽  
Author(s):  
Nubia Ponce de León Puig ◽  
Leonardo Acho ◽  
José Rodellar
Keyword(s):  
Power Efficiency ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

In the several last years, numerous Maximum Power Point Tracking (MPPT) methods for photovoltaic (PV) systems have been proposed. An MPPT strategy is necessary to ensure the maximum power efficiency provided to the load from a PV module that is subject to external environmental perturbations such as radiance, temperature and partial shading. In this paper, a new MPPT technique is presented. Our approach has the novelty that it is a MPPT algorithm with a dynamic hysteresis model incorporated. One of the most cited Maximum Power Point Tracking methods is the Perturb and Observer algorithm since it is easily implemented. A comparison between the approach presented in this paper and the known Perturb and Observer method is evaluated. Moreover, a new PV-system platform was properly designed by employing low cost electronics, which may serve as an academical platform for further research and developments. This platform is used to show that the proposed algorithm is more efficient than the standard Perturb and Observer method.

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