scholarly journals Comparative Analysis of Robustness and Tracking Efficiency of Maximum Power Point in Photovoltaic Generators, Using Estimation of the Maximum Power Point Resistance by Irradiance Measurement Processing

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7247
Author(s):  
Juan Ríos ◽  
Juan Manuel Enrique ◽  
Antonio Javier Barragán ◽  
José Manuel Andújar
Keyword(s):  
Maximum Power ◽  
Data Sets ◽  
Tracking Accuracy ◽  
Maximum Power Point ◽  
Irradiance Measurement ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Measurement Processing ◽  
Power Point ◽  
Photovoltaic Generators

The model-based methods of maximum power point (MPP) tracking in photovoltaic installations are widely known. One of these methods proposes the use of tracking by direct estimation of the maximum power point resistance using irradiance measurement processing. It proposes six different models for this estimate. In the present work, an exhaustive analysis to determine the robustness and accuracy of the different models was carried out. To perform the analysis, irradiance data sets, used to fit the parameters of the models, were collected. In addition, tests were done to determine MPP tracking accuracy of each of the six models. To carry out the tests, all models were compared with a widely used maximum power point tracking algorithm, perturb & observe, for different values of irradiance, temperature, and load.

Comparison of Methods of Maximum Power Point Tracking of Photovoltaic Cells

2013 ◽  
Vol 380-384 ◽  
pp. 3362-3365
Author(s):  
Lan Li ◽  
Yong Hui He ◽  
Bo Wang
Keyword(s):  
Control System ◽  
Maximum Power Point Tracking ◽  
Photovoltaic Cells ◽  
Maximum Power ◽  
Tracking Accuracy ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point ◽  
Observation Method

According to engineering mathematics model of solar photovoltaic cells, a simulation model of photovoltaic cells was established in Matlab. In view of problem that it is difficult to get higher tracking accuracy and response speed by use of perturbation and observation method which applied fixed perturbation step, the paper proposed an improved perturbation and observation method based on variable step. Through simulating photovoltaic cells control system, simulation curves of two kinds of methods of maximum power point tracking were compared. The simulation results show that the photovoltaic cells control system can track maximum power point more quickly and has better stability at the maximum power point by use of the improved perturbation and observation method.

Researched on Maximum Power Point Tracking of PV Power System

2012 ◽  
Vol 229-231 ◽  
pp. 1009-1012
Author(s):  
Wei Min Chen ◽  
Shuang Chen ◽  
Nan Xie ◽  
Hui Cai
Keyword(s):  
Perturbation Method ◽  
Comparison Method ◽  
Maximum Power ◽  
Tracking Accuracy ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Variable Step ◽  
External Conditions ◽  
Power Point

To the oscillation and misjudgment problem of the traditional perturbation and observation algorithm, a novel three-point comparison method was proposed. This method applied Constant Voltage Tracking (CVT) method and variable-step perturbation method to solve the problem between tracking accuracy and speed, and applied double-direction perturbation method to make sure the reliability of action to avoid the misjudgment when external conditions fast changing. Restraining the oscillation near the maximum power point effectively was another merit of this proposed method. Finally, the experimental results demonstrate effectiveness of proposed method with PV experimental platform.

scholarly journals Assessing Maximum Power Point Tracking Intelligent Techniques on a PV System with a Buck–Boost Converter

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7453
Author(s):  
Maria I. S. Guerra ◽  
Fábio M. Ugulino de Araújo ◽  
Mahmoud Dhimish ◽  
Romênia G. Vieira
Keyword(s):  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Ambient Conditions ◽  
Tracking Accuracy ◽  
Pv System ◽  
Maximum Power Point ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Classic and intelligent techniques aim to locate and track the maximum power point of photovoltaic (PV) systems, such as perturb and observe (P&O), fuzzy logic (FL), artificial neural networks (ANNs), and adaptive neuro-fuzzy inference systems (ANFISs). This paper proposes and compares three intelligent algorithms for maximum power point tracking (MPPT) control, specifically fuzzy, ANN, and ANFIS. The modeling of a single-diode equivalent circuit-based 3 kWp PV plant was developed and validated to achieve this purpose. Then, the MPPT techniques were designed and applied to control the buck–boost converter’s switching device of the PV plant. All three methods use the ambient conditions as input variables: solar irradiance and ambient temperature. The proposed methodology comprises the study of the dynamic response for tracking the maximum power point and the power generated of the PV systems, and it was compared to the classic P&O technique under varying ambient conditions. We observed that the intelligent techniques outperformed the classic P&O method in tracking speed, tracking accuracy, and reducing oscillation around the maximum power point (MPP). The ANN technique was the better control algorithm in energy gain, managing to recover up to 9.9% power.

scholarly journals Improved Perturb and Observation Method Based on Support Vector Regression

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1151 ◽  
Author(s):  
Bicheng Tan ◽  
Xin Ke ◽  
Dachuan Tang ◽  
Sheng Yin
Keyword(s):  
Support Vector Regression ◽  
Direct Current ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Support Vector ◽  
Tracking Accuracy ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Solar energy is the most valuable renewable energy source due to its abundant storage and is pollution-free. The output power of photovoltaic (PV) arrays will vary with external conditions, such as irradiance and temperature fluctuations. Therefore, an increase in the energy conversion rate is inseparable from maximum power point tracking (MPPT). The existing MPPT technology cannot either balance the tracking speed and tracking accuracy, or the implementation cost is too high due to the complexity of the calculation. In this paper, a new maximum power point tracking (MPPT) method was proposed. It improves the traditional perturb and observation (P&O) method by introducing the support vector regression (SVR) algorithm. In this method, the current maximum power point voltage is predicted by the trained model and compared with the current operating voltage to predict a reasonable step size. The boost DC/ DC (Direct current-Direct current converter) convert system applying the improved method and the traditional P&O was simulated in MATLAB-Simulink, respectively. The results of the simulation show that compared with the traditional P&O method, the proposed new method both improves the convergence time and tracking accuracy.

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