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Power grid load prediction method based on artificial intelligence

A technology of power grid load and forecasting method, applied in forecasting, electrical digital data processing, structured data retrieval, etc., can solve problems such as complex forecasting algorithms and inaccurate forecasting results, achieve accurate forecasting, accurate power load forecasting data, and avoid The effect of overfitting

Pending Publication Date: 2022-03-04
CHONGQING CREATION VOCATIONAL COLLEGE
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Problems solved by technology

[0006] The purpose of the present invention is to provide a power grid load forecasting method based on artificial intelligence, which mainly solves the problems of complex forecasting algorithms and inaccurate forecasting results of existing power grid load forecasting methods

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  • Power grid load prediction method based on artificial intelligence
  • Power grid load prediction method based on artificial intelligence
  • Power grid load prediction method based on artificial intelligence

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Embodiment 1

[0042] This embodiment is a basic implementation mode of the present invention, as figure 1 , 2 As shown, it discloses an artificial intelligence-based power grid load forecasting method, including the following steps:

[0043] Firstly, the historical power load data of the natural unit is obtained, and the time period corresponding to the natural unit of the historical power load peak value is recorded; the natural unit is a natural month or a natural day. Thus, monthly load forecasting and daily load forecasting can be realized, which is convenient for power grid dispatching.

[0044] According to the law of historical power consumption, the power load is closely related to the actual weather environment. Therefore, after obtaining the historical power load data, it is necessary to correlate the peak power load, the peak time period of the power load, and the corresponding meteorological environment data; First, preprocess the peak power load data in natural units to obtai...

Embodiment 2

[0055] This embodiment is a basic implementation mode of the present invention, as Figure 1~3 As shown, it discloses an artificial intelligence-based power grid load forecasting method, including the following steps:

[0056] Firstly, the historical power load data of the natural unit is obtained, and the time period corresponding to the natural unit of the historical power load peak value is recorded; the natural unit is a natural month or a natural day. Thus, monthly load forecasting and daily load forecasting can be realized, which is convenient for power grid dispatching.

[0057] According to the law of historical power consumption, the power load is closely related to the actual weather environment. Therefore, after obtaining the historical power load data, it is necessary to correlate the peak power load, the peak time period of the power load, and the corresponding meteorological environment data; First, preprocess the peak power load data in natural units to obtain ...

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Abstract

The invention discloses a power grid load prediction method based on artificial intelligence. The problems that an existing power grid load prediction method is complex in prediction algorithm and inaccurate in prediction result are mainly solved. The prediction method comprises the following steps: acquiring historical power load data, determining a historical power load peak time section, preprocessing the historical power load peak data to obtain mapping data of the processed power load peak data and distribution characteristics of meteorological environment data, and meanwhile, obtaining the meteorological environment data through data preprocessing. And finally determining a training set of the initial training model. A data model is obtained by training a data set of the training set, and a power load prediction model is established. Therefore, the power load of the corresponding time section can be predicted by inputting the predicted meteorological environment data, fitting calculation is not needed, meanwhile, the over-fitting phenomenon existing in the prior art is effectively avoided, the influence of the over-fitting phenomenon on the model precision is also avoided, and accurate prediction of the future power load is facilitated.

Description

technical field [0001] The invention belongs to the technical field of electric load detection, and in particular relates to an artificial intelligence-based power grid load prediction method. Background technique [0002] Carbon neutrality, a term for energy conservation and emission reduction, refers to the calculation of the total amount of greenhouse gas emissions directly or indirectly produced by an enterprise, group or individual within a certain period of time, and offsets the amount of greenhouse gas emissions generated by itself through afforestation, energy conservation and emission reduction, etc. carbon dioxide emissions, to achieve "zero emissions" of carbon dioxide. Carbon peaking refers to the period when carbon emissions enter a plateau and then enter a stage of steady decline. Simply put, it is to "break even" on carbon dioxide emissions. [0003] Global warming is the consequence of changes in the Earth's climate caused by human actions. "Carbon" refers...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06F16/21G06F16/2458
CPCG06Q10/04G06Q50/06G06F16/212G06F16/2465
Inventor 张书波
Owner CHONGQING CREATION VOCATIONAL COLLEGE
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