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A Solar Tracking Control System Based on Neural Network Prediction Technology

A technology of solar tracking and forecasting technology, which is applied to biological neural network models, information technology support systems, and use feedback control, etc. It can solve the problem that it is difficult to accurately predict the power generation of photovoltaic panels, and achieve the effect of high data accuracy

Active Publication Date: 2021-08-31
无锡十一新能源投资有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the above-mentioned common mathematical model is difficult to accurately predict the non-linearly changing generating power. The present invention provides a solar tracking control system based on neural network prediction technology, thereby solving the problem that the common mathematical model is difficult to accurately predict The problem of the generated power of the panel within the delta time; at the same time, the present invention is based on the above-mentioned solar tracking control system based on neural network prediction technology, and also provides a solar tracking control method based on neural network prediction technology

Method used

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  • A Solar Tracking Control System Based on Neural Network Prediction Technology
  • A Solar Tracking Control System Based on Neural Network Prediction Technology
  • A Solar Tracking Control System Based on Neural Network Prediction Technology

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Embodiment 1

[0037] Such as figure 1 As shown, a solar tracking control system based on neural network prediction technology includes sequentially connected photovoltaic panels, a first data acquisition module, a first BP prediction module, a central controller, an execution module, and a four-axis air pressure device;

[0038] The central controller is also connected with a comparison detection module, a PID control module is arranged between the central controller and the first data acquisition module, the input end of the PID control module is connected to the output end of the first data acquisition module, and the PID The output end of the control module is connected to the input end of the central controller.

[0039] Photovoltaic panels are used to receive sunlight and convert the light energy of sunlight into electrical energy for storage;

[0040] The first data collection module is used to collect the real-time angle, real-time power generation and real-time time data of the pho...

Embodiment 2

[0048]On the basis of Embodiment 1, this embodiment optimizes the comparison detection module. The second data acquisition module of the comparison detection module is used to collect the real-time direct sunlight angle, and the power generation after the angle adjustment of the photovoltaic panel is calculated through the second BP prediction module. The power is transmitted to the central controller; the first data acquisition module is used to collect the real-time angle, real-time power generation power and real-time time data of the photovoltaic panel, the real-time angle is transmitted to the PID control module, and the real-time power generation and real-time time data are transmitted to the first A BP prediction module.

Embodiment 3

[0050] On the basis of Embodiment 1, this embodiment optimizes the setting position of the first data acquisition module, which is installed on the photovoltaic panel, which can reduce the volume of the entire system and reduce the path of data transmission, so that the collected data is accurate and reliable .

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Abstract

The invention discloses a solar tracking control system based on neural network prediction technology, which includes sequentially connected photovoltaic panels, a first data acquisition module, a first BP prediction module, a central controller, an execution module and a four-axis air pressure device; The central controller is also connected with a comparison detection module, and a PID control module is arranged between the central controller and the first data acquisition module, which can accurately calculate the power generation of the photovoltaic panel, and can accurately determine whether the photovoltaic panel needs to be adjusted, thereby Reach the purpose of energy-saving; The present invention also announces a kind of solar tracking control method based on neural network prediction technology simultaneously, this method first by setting up the first BP neural network prediction model, prediction result and curve fitting, at first model adjustment, prediction Results The method of rolling forecast is adopted, and the curve fitting is fitted by the least square method, which makes the predicted power generation more accurate and reliable.

Description

technical field [0001] The invention belongs to the technical field of solar tracking, and in particular relates to a solar tracking control system based on a neural network prediction technology. At the same time, the invention also discloses a solar tracking control method based on a neural network prediction technology. Background technique [0002] Under the situation of energy crisis, solar photovoltaic power generation has been widely developed and applied as a renewable clean energy. In the process of predicting the power generation of photovoltaic panels, there are many factors that affect the power generation of photovoltaic panels, such as energy consumption for driving the angle adjustment of photovoltaic panels, dust loss, line loss and battery efficiency, etc., making the prediction model a complex non- linear model. [0003] It is difficult for the existing general mathematical model to accurately predict the power generation within the delta time, resulting i...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D3/20G06N3/08H02S20/32
CPCG05D3/20G06N3/084H02S20/32Y02E10/50Y02E40/70Y04S10/50
Inventor 赵振元余才志谢丽娟赵远远
Owner 无锡十一新能源投资有限公司
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