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Green energy prediction method based on combination of LSTM and Attention

A technology of green energy and prediction method, applied in the field of cloud computing, can solve the problem of new energy instability hindering the wide application of new energy, and achieve the effect of reducing training time, improving prediction accuracy, and optimizing prediction results

Inactive Publication Date: 2020-08-21
BEIJING UNIV OF TECH
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Problems solved by technology

The instability of new energy seriously hinders the widespread application of new energy

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  • Green energy prediction method based on combination of LSTM and Attention
  • Green energy prediction method based on combination of LSTM and Attention
  • Green energy prediction method based on combination of LSTM and Attention

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Embodiment Construction

[0019] In order to illustrate the present invention more clearly, the present invention will be further described below in conjunction with preferred embodiments and accompanying drawings. Similar parts in the figures are denoted by the same reference numerals. Those skilled in the art should understand that the content specifically described below is illustrative rather than restrictive, and should not limit the protection scope of the present invention.

[0020] Such as figure 1 , figure 2 As shown, a green energy prediction method based on the combination of LSTM and Attention disclosed in the present invention includes the following steps:

[0021] Step 1: Preprocess the collected solar radiation and wind speed time series, and use the SG filter method to improve data accuracy

[0022] The data points in the specified window are fitted by a low-order polynomial, the parameter estimation of the low-order polynomial is realized by the least square method, and then the fi...

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Abstract

The invention discloses a green energy prediction method based on combination of LSTM and Attention. Energy supply of green renewable energy sources such as solar energy and wind energy to the cloud data center is comprehensively considered, solar energy or wind energy data in the next time period are obtained according to prediction and converted into electric energy, finally data support is provided for related departments, and early-stage preparation is made for hybrid energy complementary power supply. According to the method, wind energy and solar energy are processed by adopting an SG filtering algorithm; then, an LSTM time sequence modeling method is used for establishing a prediction model, an Attention mechanism is introduced, the mechanism can reduce the model training time, thecomplexity is low, global connection and local connection can be considered in one step, the prediction result is optimized, and the prediction precision is improved.

Description

technical field [0001] The invention belongs to the technical field of cloud computing, and in particular relates to a green energy prediction method based on the combination of LSTM and Attention. Background technique [0002] Against the backdrop of cloud computing sweeping the world and the development of the cloud computing industry surging, building green data centers and realizing energy conservation and emission reduction have become one of the topics that academic and industrial circles have paid attention to in recent years. In today's society, with the gradual expansion of the global influence of large-scale cloud computing data and the widespread deployment of cloud computing data centers around the world, in order to promote its development and better adapt to the pace of the times, cloud computing data is in high The consideration of energy consumption, high cost expenditure, high environmental pollution, etc. is increasingly showing its importance. In the new ...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06N3/04G06N3/08
CPCG06Q10/04G06Q50/06G06N3/049G06N3/08G06N3/045
Inventor 张晓芬刘恒毕敬
Owner BEIJING UNIV OF TECH