Photovoltaic Arrays MPPT Based on Improved Incremental Conductance Method

2012 ◽  
Vol 608-609 ◽  
pp. 177-180
Author(s):  
Xuan He ◽  
Wen Yi Li ◽  
Xiu Li ◽  
Li Guo ◽  
Yan Wang ◽  
...  
Keyword(s):  
Photovoltaic Cell ◽  
Characteristic Analysis ◽  
Maximum Power Point ◽  
Advantages And Disadvantages ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Photovoltaic Arrays ◽  
Conductance Method ◽  
Output Characteristics ◽  
Power Point

This paper analyzes advantages and disadvantages of different maximum power point tracking (MPPT) methods based on mathematical model of photovoltaic cell and its characteristic analysis. According to output characteristics of photovoltaic (PV) array, this paper puts forwards an improved increment conductance (INC) method which can improve the efficiency of photovoltaic cell by increasing power tracking speed under the premise of ensuring stability of the system. This method is verified by means of MATLAB/Simulink.

A New Scheme Based on Climbing Method for Maximum Photovoltaic Power Tracking Control

2014 ◽  
Vol 707 ◽  
pp. 377-380
Author(s):  
Bo Qiang Xu ◽  
Jin Bo Li
Keyword(s):  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Variable Step Size ◽  
Step Size ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Photovoltaic Arrays ◽  
Conductance Method ◽  
Power Point

The maximum power point tracking (MPPT) of photovoltaic arrays can increase the output power of the photovoltaic systerm, improve the utilization of solar energy. This paper describes the output characteristics of the photovoltaic arrays and the principle of maximum power point tracking,then,based on Incremental conductance method, proposes a sub-type of the variable step size MPPT algorithm. simulated using MATLAB/Simulink, the final results show that the proposed algorithm is able to quickly track the maximum power point and power concussion problem has been significantly improved.

scholarly journals Modeling and Simulation of an Intelligent Photovoltaic Controller Based on Variable Step Algorithm of Versoria

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Bo Sun ◽  
Yongquan You ◽  
Zhiyong Zhang ◽  
Chao Li
Keyword(s):  
Control Algorithm ◽  
Photovoltaic Cells ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Step Algorithm ◽  
Output Characteristics ◽  
Power Point ◽  
Fuzzy Control Algorithm

As a green and renewable energy source, photovoltaic power is of great significance for the sustainable development of energy and has been increasingly exploited. The photovoltaic controller is the key component of a photovoltaic power generation system, and its central technology is the maximum power point tracking technology. In this paper, a mathematical model of photovoltaic cells is firstly established, the output characteristics of photovoltaic cells are analyzed, the main factors that affect the output efficiency of photovoltaic cells are obtained, and it is proved that the most important factor that affects the output power is the light intensity. Therefore, in the design, the maximum power point of the photovoltaic cell is tracked by the control algorithm and can maximize the use of photovoltaic output power fast charging. The key to the design of a photovoltaic controller is the design of control algorithm. So, an improved fuzzy control algorithm is proposed to overcome the shortcomings of the traditional maximum power point tracking (MPPT) algorithm. The algorithm can consider tracking both speed and convergence, but the algorithm requires high input and output fuzzy domain parameters, and although the tracking speed is fast, the stability of convergence is poor. For the limitation of fuzzy control algorithm, considering the property of the Versoria function, an MPPT design method for an intelligent controller based on the Versoria variable step algorithm is further proposed. According to the output characteristics of photovoltaic cells, three parameters, α, β, and γ, are set to solve the tracking speed and tracking stability. In order to reduce the static error, a genetic factor is proposed to sum up the historical error to effectively improve the tracking stability. The simulation results show that the algorithm can track the maximum power point quickly and has good tracking speed and stability. This algorithm can be used in engineering practice effectively.

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