scholarly journals Application of Fuzzy Control in a Photovoltaic Grid-Connected Inverter

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Zhaohong Zheng ◽  
Tianxia Zhang ◽  
Jiaxiang Xue
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
Control Method ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Grid Connected Inverter ◽  
Power Point ◽  
Fuzzy Control Algorithm

To realize the maximum power output of a grid-connected inverter, the MPPT (maximum power point tracking) control method is needed. The perturbation and observation (P&O) method can cause the inverter operating point to oscillate near the maximum power. In this paper, the fuzzy control P&O method is proposed, and the fuzzy control algorithm is applied to the disturbance observation method. The simulation results of the P&O method with fuzzy control and the traditional P&O method prove that not only can the new method reduce the power loss caused by inverter oscillation during maximum power point tracking, but also it has the advantage of speed. Inductive loads in the post-grid-connected stage cause grid-connected current distortion. A fuzzy control algorithm is added to the traditional deadbeat grid-connected control method to improve the quality of the system’s grid-connected operation. The fuzzy deadbeat control method is verified by experiments, and the harmonic current of the grid-connected current is less than 3%.

A Photovoltaic MPPT Strategy by Modified Fuzzy Control

2011 ◽  
Vol 128-129 ◽  
pp. 15-19
Author(s):  
Bo Fu ◽  
Lu Yu ◽  
Qiong Cheng ◽  
Xin Chen Cai ◽  
Xin Xing
Keyword(s):  
Fuzzy Control ◽  
Control Algorithm ◽  
Control Method ◽  
Superior Performance ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point ◽  
Fuzzy Control Algorithm ◽  
Time Delayed Feedback

Maximum Power Point Tracking control method based on traditional fuzzy algorithm has disadvantages of slow response and unstable output. To solve the problems, a modified fuzzy control algorithm by combining the traditional two-dimensional fuzzy control with a time-delayed feedback is proposed. It not only fast responds to the changes in ambient environment but also has good stability. Simulation results show that the proposed algorithm has superior performance to the traditional fuzzy control.

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.

The Research of Maximum Power Point Tracking Based on Fuzzy Control in Grid-Connected Photovoltaic System

2012 ◽  
Vol 512-515 ◽  
pp. 202-207
Author(s):  
Qiang Xu ◽  
Xiao Chun Zhang ◽  
Kai Chun Ren ◽  
Xing Qi Zhang ◽  
Xiao Jun Liu
Keyword(s):  
Solar Cells ◽  
Fuzzy Control ◽  
Control Method ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

This paper analyzes the characteristics of solar cells, and establishes the simulation model from its mathematical expressions which can factually reflects the change of solar cells’ parameters. The commonly used method of maximum power point tracking technologies is introduced. A PV system’s most maximum power is simulated by using the fuzzy control method. Simulation results show that the system can work at a stable maximum power point rapidly.

A Research on the Fuzzy Control with Genetic Algorithm for Maximum Power Point Tracking of Photovoltaic Power System

2013 ◽  
Vol 303-306 ◽  
pp. 1153-1157
Author(s):  
Yi Zong Dai ◽  
De Jun Miao
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Control ◽  
Fuzzy Controller ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Point ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Based on the nonlinear of the photovoltaic device output power and the frequent changes in the work environment, a fuzzy controller with genetic algorithm was applied to maximum power point tracking (MPPT) of photovoltaic generation system. The problem of difference in the different interval of the maximum point was solved. It ensure that the system has a higher accuracy .By comparing the method of the fuzzy control and the method of fuzzy control with genetic algorithm through simulation , the result demonstrates the better control effect.

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