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Maximum power tracker control method based on generalized dynamic fuzzy neural network

A technology of maximum power tracking and fuzzy neural network, which is applied in the field of grid-connected solar energy, can solve the problem of weak adaptive ability of maximum power control

Inactive Publication Date: 2017-03-22
LOGISTICAL ENGINEERING UNIVERSITY OF PLA
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Problems solved by technology

[0003] The object of the present invention is to provide a maximum power tracker control method based on a generalized dynamic fuzzy neural network, aiming at solving the problem that the existing maximum power control is not strong in self-adaptation

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  • Maximum power tracker control method based on generalized dynamic fuzzy neural network
  • Maximum power tracker control method based on generalized dynamic fuzzy neural network
  • Maximum power tracker control method based on generalized dynamic fuzzy neural network

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[0058]In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0059] The application principle of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0060] Aiming at the characteristics of the photovoltaic system, the invention proposes a maximum power tracker control method based on a generalized dynamic fuzzy neural network. And compared with the control method using fuzzy reasoning, the results show that the control method based on generalized dynamic fuzzy neural network (GD-FNN) can track the changes of the external environment and realize the maximum output of power.

[0061] The application principle of the present invention...

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Abstract

The invention discloses a maximum power tracker control method based on a generalized dynamic fuzzy neural network. The method is provided on the basis of the fuzzy neural network algorithm; the method includes adopting the fuzzy completeness based on elliptic basis function as an on-line distribution mechanism to avoid randomness of the initial selection; evaluating the importance of fuzzy rules, and responding to the importance of input variables; implementing on-line real-time adaptive adjustment of the width of the input variables of each rule according to the requirements of system performance. According to the method, the maximum power point can be found rapidly in 0.01 second by the aid of the generalized dynamic fuzzy neural network theory simulation results, the problem of oscillation of the maximum power point can be overcome effectively, and the robustness and fastness are high.

Description

technical field [0001] The invention belongs to the technical field of grid-connected solar energy, and in particular relates to a maximum power tracker control method based on a generalized dynamic fuzzy neural network. Background technique [0002] Human beings use coal, oil and other conventional fossil fuels without restraint, but the reserves of this non-renewable conventional energy are limited, and will be exhausted sooner or later, and the combustion of fossil fuels emits a large amount of carbon dioxide, Gases such as sulfur dioxide are the chief culprits of the current severe environmental pollution. Ecological damage caused by environmental pollution and the global warming effect are increasingly threatening the survival and sustainable development of human beings. Energy shortage and environmental pollution are two major problems facing the world today, which have seriously restricted the development of human economy and society. Facing the energy crisis that i...

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Application Information

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IPC IPC(8): G05F1/67
CPCG05F1/67
Inventor 袁韬易斌王海龙杨静周凌王锐淇
Owner LOGISTICAL ENGINEERING UNIVERSITY OF PLA
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