Day-ahead power load prediction method and device based on double-end automatic coding

A technology of electric load and automatic coding, which is applied in forecasting, neural learning methods, instruments, etc., can solve the problems of feature redundancy, model difficulty in accurate modeling, and high dimensionality

Pending Publication Date: 2020-05-12
天津相和电气科技有限公司 +2
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AI Technical Summary

Problems solved by technology

[0004] The main problem of day-ahead load forecasting is that the operation of load has a time-dependent relationship, and load changes in the past period of time often have a greater impact on the load of the next day
However, when historical load is used as a feature, its dimen...

Method used

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  • Day-ahead power load prediction method and device based on double-end automatic coding
  • Day-ahead power load prediction method and device based on double-end automatic coding
  • Day-ahead power load prediction method and device based on double-end automatic coding

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Embodiment 1

[0051] Such as Figure 1-8 As shown, in the day-ahead power load forecasting method based on double-ended autocoding provided by this embodiment, the day-ahead power load forecasting method includes the following steps:

[0052] S1. Obtain the historical power load data and the characteristics of the influencing factors that need to be considered to affect the power load, and form a database of historical power load and influencing factors characteristics;

[0053] In this embodiment, the load data of M days before the day-ahead power load forecast date is acquired as the historical power load data, assuming that the load data of the N days before a certain moment is used to predict the load data of the next day at that moment;

[0054] Among them, the method for obtaining the characteristic data of historical power load and influencing factors is as follows:

[0055] S101. Analyze the influence of meteorological and social factors on the power load, and obtain the meteorolog...

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Abstract

The invention relates to a day-ahead power load prediction method based on double-end automatic coding, and the method comprises the following steps: obtaining influence factor features which need tobe considered and have an influence on a power load, and forming a historical power load and influence factor feature database; constructing an auto-encoder 1, training the auto-encoder 1, and inputting historical power load characteristic data into the trained auto-encoder 1 to obtain a fused data set; constructing a neural network, training the neural network, and inputting the obtained fused data set into the trained neural network for power load prediction; constructing an auto-encoder 2, and training the auto-encoder 2; inputting the obtained power load prediction data into the trained auto-encoder 2; performing reverse normalization on the obtained decoded power load prediction data to obtain final day-ahead power load data. According to the method, the dimension problem in day-aheadload prediction is solved, and the precision of day-ahead load prediction is improved.

Description

technical field [0001] The invention belongs to the technical field of intelligent power distribution and utilization, and in particular relates to a day-ahead power load forecasting method and device based on double-ended automatic coding. Background technique [0002] Load forecasting is an important basic analysis tool for energy management and optimal scheduling of large power grids. It can guide power companies to economically and rationally arrange the start-stop and maintenance plans of generating units, guarantee the normal production and life of the society, effectively reduce power generation costs, and improve economic efficiency. benefits and social benefits. At the same time, load forecasting is also a basic function and an important analysis tool for intelligent power distribution. The development and construction of intelligent power distribution takes safety and reliability, high quality and efficiency, and flexible interaction as the main goals, and puts fo...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06N3/04G06N3/08
CPCG06Q10/04G06Q50/06G06N3/08G06N3/045
Inventor 王守相陈海文蔡声霞付丽伟
Owner 天津相和电气科技有限公司
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