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Solar photovoltaic controller based on adaptive neural network

A solar photovoltaic and neural network technology, applied in the field of solar photovoltaic controllers, can solve the problem of inability to optimally control the maximum output power in real time, and achieve the effect of attenuating switching frequency harmonics

Pending Publication Date: 2022-04-12
ZHEJIANG UNIV
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  • Abstract
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  • Application Information

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Problems solved by technology

[0003] Aiming at the problem that the current traditional solar photovoltaic system cannot optimally control the maximum output power in real time for a series of environmental changes such as solar radiation and temperature, the present invention provides a solar photovoltaic controller based on an adaptive neural network, which can effectively and quickly track Maximum power of solar photovoltaic arrays under different climate conditions

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  • Solar photovoltaic controller based on adaptive neural network
  • Solar photovoltaic controller based on adaptive neural network
  • Solar photovoltaic controller based on adaptive neural network

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Embodiment Construction

[0007] The invention provides a solar photovoltaic controller based on an adaptive neural network, which includes an adaptive fuzzy neural network controller module, a DC link capacitor module and an LCL filter module. Each module is connected sequentially, the adaptive fuzzy neural network controller module is used to maximize the conversion efficiency of the photovoltaic array, and the DC link capacitor module is used to buffer power fluctuation loss and decouple the DC converter and the AC inverter , LCL filter block for attenuating excessive switching frequency harmonics.

[0008] The adaptive fuzzy neural network controller module is used to maximize the conversion efficiency of the photovoltaic array, and its network structure is as follows:

[0009] (1.1) The first layer network: each node of the training data is an adaptive node, and the node function is expressed as follows:

[0010] A 1,i =μX i (x) for i=1,2 (1)

[0011] A 1,i =μY i -2(y) for i=3,4 (2)

[0012...

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Abstract

The invention discloses a solar photovoltaic system controller based on an adaptive neural network. The solar photovoltaic system controller is composed of an adaptive fuzzy neural network controller module, a direct current link capacitor module and an LCL filter module which are connected in sequence. According to the invention, the defect that the existing traditional controller is unstable is overcome, the oscillation is small, the dynamic response is fast, and the maximum power of the solar photovoltaic array under different weather conditions can be tracked more effectively and quickly.

Description

technical field [0001] The invention relates to the field of solar photovoltaic systems, in particular to a solar photovoltaic controller based on an adaptive neural network. Background technique [0002] The environmental problems caused by the consumption of traditional fossil fuels have attracted more and more people's attention, and the new power generation technology represented by solar photovoltaic power generation has become a new frontier of science and technology. However, solar photovoltaic power generation is affected by many aspects such as solar radiation and temperature. There is an urgent need to more efficiently and quickly track the maximum power of solar photovoltaic arrays under different climatic conditions. Contents of the invention [0003] Aiming at the problem that the current traditional solar photovoltaic system cannot optimally control the maximum output power in real time for a series of environmental changes such as solar radiation and temper...

Claims

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Application Information

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IPC IPC(8): H02J3/38G06N3/04G06N3/063G06N3/08
CPCY02E10/56Y02E40/70Y04S10/50
Inventor 阿卜杜拉刘兴高
Owner ZHEJIANG UNIV