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A photovoltaic power generation power prediction method based on deep learning

A technology of photovoltaic power generation and prediction method, which is applied in the direction of prediction, electrical digital data processing, instruments, etc., can solve the problems of lack of theoretical analysis and large error of photovoltaic power generation, and solve the problem of inaccurate prediction of power generation and high prediction rate , Improve the effect of security and confidentiality

Pending Publication Date: 2019-05-07
NANTONG INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, there is a lack of theoretical analysis on the selection of meteorological factors, which leads to large errors in the photovoltaic power generation determined in advance

Method used

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  • A photovoltaic power generation power prediction method based on deep learning
  • A photovoltaic power generation power prediction method based on deep learning
  • A photovoltaic power generation power prediction method based on deep learning

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Embodiment 1

[0045] see Figure 1-3 , the present invention provides the following technical solution: a method for predicting photovoltaic power generation based on deep learning, comprising the following steps:

[0046] A. Collect photovoltaic power generation data and preprocess the collected data;

[0047] B. Send the preprocessed data to the memory for storage;

[0048] C. Extract features from the stored photovoltaic power generation data;

[0049] D. Then encrypt the data after feature extraction;

[0050] E. The encrypted data is used as the input of the BP neural network, and the output of the BP neural network is the photovoltaic power generation power to be predicted, and multiple sets of neural network prediction models are established;

[0051] F. Conduct in-depth training on multiple sets of neural network prediction models, and select the neural network prediction model corresponding to the best performance parameters as the final prediction model to predict the photovolt...

Embodiment 2

[0069] A method for predicting photovoltaic power generation based on deep learning, comprising the following steps:

[0070] A. Collect photovoltaic power generation data and preprocess the collected data;

[0071] B. Send the preprocessed data to the memory for storage;

[0072] C. Extract features from the stored photovoltaic power generation data;

[0073] D. Then encrypt the data after feature extraction;

[0074] E. The encrypted data is used as the input of the BP neural network, and the output of the BP neural network is the photovoltaic power generation power to be predicted, and multiple sets of neural network prediction models are established;

[0075] F. Conduct in-depth training on multiple sets of neural network prediction models, and select the neural network prediction model corresponding to the best performance parameters as the final prediction model to predict the photovoltaic power generation.

[0076] First collect photovoltaic data, preprocess the coll...

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Abstract

The invention discloses a photovoltaic power generation power prediction method based on deep learning. The photovoltaic power generation power prediction method comprises the following steps: A, acquiring photovoltaic power generation data and sending the photovoltaic power generation data to a memory for storage; B, performing feature extraction on the stored photovoltaic power generation data;C, encrypting the data subjected to feature extraction; D, using the encrypted data as input of a BP neural network, wherein the output of the BP neural network is to-be-predicted photovoltaic power generation power; And E, performing deep training on the BP neural network to obtain the photovoltaic power generation prediction power. The prediction method is high in precision and prediction rate,and the adopted data preprocessing method can realize data sorting, noise reduction and data filtering, so that the subsequent data processing efficiency is improved; According to the adopted featureextraction method, the first keyword and the second keyword are searched, so that the extraction difficulty can be reduced, and the feature extraction precision is improved; The adopted encryption method can perform multiple encryption on the photovoltaic data, so that the security and confidentiality of the data are improved.

Description

technical field [0001] The invention relates to the technical field of photovoltaic power generation forecasting, in particular to a method for forecasting photovoltaic power generation power based on deep learning. Background technique [0002] Photovoltaic power generation is a technology that directly converts light energy into electrical energy by using the photovoltaic effect at the semiconductor interface. It is mainly composed of three parts: solar panels (components), controllers and inverters, and the main components are composed of electronic components. The solar cells are packaged and protected after being connected in series to form a large-area solar cell module, and then cooperate with power controllers and other components to form a photovoltaic power generation device. The main principle of photovoltaic power generation is the photoelectric effect of semiconductors. When a photon irradiates a metal, its energy can be completely absorbed by an electron in t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06F16/215G06F16/2458G06F21/60
Inventor 郭亚琴顾娜
Owner NANTONG INST OF TECH
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