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Method for adjusting duty ratio based on neural network to realize maximum power tracing

A technology of maximum power tracking and neural network, applied in the direction of adjusting electrical variables, control/regulation systems, instruments, etc., can solve the problem of high cost and achieve the effect of avoiding oscillation, fast and accurate maximum power output

Inactive Publication Date: 2019-04-16
FUZHOU UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

However, dU and dI are relatively small, requiring sensors with high precision and high cost

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  • Method for adjusting duty ratio based on neural network to realize maximum power tracing
  • Method for adjusting duty ratio based on neural network to realize maximum power tracing
  • Method for adjusting duty ratio based on neural network to realize maximum power tracing

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Embodiment Construction

[0042] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0043]It should be pointed out that the following detailed description is exemplary and is intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0044] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinat...

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Abstract

The invention relates to a method for adjusting a duty ratio based on a neural network to realize maximum power tracing. Since a disturbance observation method has the defects of relatively slow convergence and difficulty in determining a maximum power point through oscillation, the disturbance observation method is improved, so that the method of the invention is provided. According to the methodof the invention, a BP neural network is adopted to establish the model of and predict the maximum power point of solar power generation; at the beginning, a voltage is directly adjusted, so that thevoltage reaches a predicted maximum value, and therefore, a condition that MPPT tracking for searching a true maximum power point tightly follows an intermediate process for finding a maximum power point can be avoided; when previous power output and later power output are equal or are within a certain range, the maximum power point is adjusted to be the median value of the previous power outputand later power output on the basis that the two sides of a P-U characteristic curve are close to be in symmetry, so that the maximum power point is closer to the true maximum output power point.

Description

technical field [0001] The invention relates to the field of maximum power tracking of solar power generation, in particular to a method for adjusting a duty cycle based on a neural network to realize maximum power tracking. Background technique [0002] The fossil energy on the earth is limited, and with the increase of people's demand for energy, the fossil energy is decreasing at a visible speed, and it has brought environmental damage, energy problems and other consequences. On the contrary, the amount of solar energy stored on the earth is infinite and clean, so solar photovoltaic power generation, as a power generation method with unlimited potential, deserves our efforts to study. At the same time, photovoltaic power generation has uncertainty and unpredictability, and the maximum output power can effectively use solar energy. Therefore, improving technology can effectively help the development of household photovoltaic power generation, and change the power output by...

Claims

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Application Information

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IPC IPC(8): G05F1/67
CPCG05F1/67
Inventor 苏文聪戴秋红金涛
Owner FUZHOU UNIV
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