Photovoltaic system optimization by new maximum power point tracking (MPPT) models based on analog components under harsh condition

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Minh Long Hoang

Abstract Photovoltaic (PV) energy has become a promising energy source because the demand for electrical energy from renewable energy sources is increasing worldwide in recent decades. Due to efficiency issues, the Maximum Power Point Tracking (MPPT) has been developed to optimize the solar panel’s performance. This paper presents an MPPT model, made up of the analog component, which overcomes traditional MPPT methods’ weakness via the Perturb and observes (P&O) technique. In this case, the PV system includes a PV array, a DC/DC boost converter, a battery, and a load. The proposed method was precisely built and simulated using the Powersim, MATLAB Simulink, and SimCoupler Module. The components of the analog MPPT system were designed practically in detail. The experiment was carried out by using European Efficiency Test 50530, and the results showed the proposed model has higher efficiency over the digital MPPT technique, about 99.99% as maximum. Moreover, MPPT methods were tested under steady-state, irradiation variation, and space conditions to verify the system’s potential capability with PV module Solbian 52L.

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1866 ◽  
Author(s):  
Nubia Ponce de León Puig ◽  
Leonardo Acho ◽  
José Rodellar

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.


2015 ◽  
Vol 12 (1) ◽  
pp. 15 ◽  
Author(s):  
R. Ramaprabha ◽  
S.P. Chitra

Mismatching effects due to partial shaded conditions are the major drawbacks existing in today’s photovoltaic (PV) systems. These mismatch effects are greatly reduced in distributed PV system architecture where each panel is effectively decoupled from its neighboring panel. To obtain the optimal operation of the PV panels, maximum power point tracking (MPPT) techniques are used. In partial shaded conditions, detecting the maximum operating point is difficult as the characteristic curves are complex with multiple peaks. In this paper, a neural network control technique is employed for MPPT. Detailed analyses were carried out on MPPT controllers in centralized and distributed architecture under partial shaded environments. The efficiency of the MPPT controllers and the effectiveness of the proposed control technique under partial shaded environments was examined using MATLAB software. The results were validated through experimentation. 


2018 ◽  
Vol 7 (3) ◽  
pp. 94-111 ◽  
Author(s):  
Hanane Yatimi ◽  
Elhassan Aroudam

In this article, on the basis of studying the mathematical model of a PV system, a maximum power point tracking (MPPT) technique with variable weather conditions is proposed. The main objective is to make a full utilization of the output power of a PV solar cell operating at the maximum power point (MPP). To achieve this goal, the incremental conductance (IC) MPPT technique is applied to an off-grid PV system under varying climatic conditions, in particular, solar irradiance and temperature that are locally measured in Northern Morocco. The output power behavior and the performance of the system using this technique have been analyzed through computer simulations to illustrate the validity of the designed method under the effect of real working conditions.


2016 ◽  
Vol 39 (2) ◽  
pp. 244-256 ◽  
Author(s):  
Qichang Duan ◽  
Mingxuan Mao ◽  
Pan Duan ◽  
Bei Hu

In a photovoltaic (PV) system, maximum power point tracking (MPPT) under partial shading (PS) conditions is a challenging task due to the presence of multiple peaks in the power voltage characteristics. This paper puts forward a novel artificial fish-swarm algorithm (FSA), which is optimized by particle swarm optimization with extended memory (PSOEM-FSA). In this algorithm, both the velocity inertia factor and the memory and learning capacity of PSOEM are introduced into the FSA. To validate the effectiveness of the novel algorithm, the PV system along with the proposed MPPT algorithm was simulated using Matlab/Simulink Simscape tool box. The simulation results show that the proposed approach is effective in MPPT under PS conditions and has a more stable performance when compared with the traditional methods in convergence speed and searching precision.


Author(s):  
Imad A. Elzein ◽  
Yuri N. Petrenko

In this article an extended literature surveying review is conducted on a set of comparative studies of maximum power point tracking (MPPT) techniques.  Different MPPT methods are conducted with an ultimate aim of how to be maximizing the PV system output power by tracking Pmax in a set of different operational circumstances. In this paper maximum power point tracking, MPPT techniques are reviewed on basis of different parameters related to the design simplicity and or complexity, implementation, hardware required, and other related aspects.


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.


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