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DLSTM power load prediction method and device based on meteorological parameters

A technology of electric load and meteorological parameters, applied in the field of electric power, to achieve the effect of good load forecasting

Pending Publication Date: 2021-06-29
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Furthermore, SVM or improved SVR are mostly used in the load forecasting of existing relevant meteorological parameters. These methods have some shortcomings caused by the characteristics of traditional shallow machine learning.

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  • DLSTM power load prediction method and device based on meteorological parameters
  • DLSTM power load prediction method and device based on meteorological parameters
  • DLSTM power load prediction method and device based on meteorological parameters

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Embodiment Construction

[0054] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0055] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0056] like figure 1 Shown, the present invention provides a kind of method based on the DLSTM electric load forecasting of meteorological parameter comprising:

[0057] Step 1. Obtain the historical data related...

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Abstract

The invention discloses a DLSTM power load prediction method and device based on meteorological parameters, and the method comprises the steps: 1, obtaining historical data related to the power load prediction, constructing a data set, and carrying out the preprocessing of the data set; 2, building a power load prediction model based on a DLSTM neural network, and training the power load prediction model by using the preprocessed data set; and 3, performing power load prediction on the acquired real-time data according to the trained power load prediction model. By adopting the technical scheme of the invention, the key factor weather in the power load and the deep learning method of the DLSTM are combined, the method can be better used for load prediction, and the construction of a power load prediction model with high cost performance is facilitated.

Description

technical field [0001] The invention belongs to the technical field of electric power, and in particular relates to a DLSTM electric load forecasting method and device based on meteorological parameters. Background technique [0002] Electricity is a basic commodity in daily life, but the production of electric power must be reasonably arranged according to the demand and utilization rate of electric power, and large-scale storage of electric energy cannot yet be realized, too much or too little power production is not conducive to the power system Efficient, economical and stable operation. Therefore, how to combine various factors to design a low-cost and high-performance power load forecasting model to better predict future power consumption trends, dispatch generators, and ensure uninterrupted energy supply for consumers is a technology to be solved one of the problems. Studies have shown that the power consumption of households and businesses for heating and cooling i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06Q10/04G06Q50/06G06N3/04G06N3/08
CPCG06F30/27G06Q10/04G06Q50/06G06N3/08G06N3/044
Inventor 龚钢军孟芷若马洪亮武昕文亚凤陆俊苏畅
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)