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Short-term load prediction method and system based on principal component analysis, and terminal equipment

A short-term load forecasting and principal component analysis technology, applied in the field of power system load, can solve the problems of low forecasting accuracy, limited model usage scenarios, affecting the optimal scheduling of power systems and market operation efficiency, etc., so as to improve forecasting accuracy and reduce impact. Effect

Pending Publication Date: 2020-09-18
GUANGDONG POWER GRID CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The embodiment of the present invention provides a short-term load forecasting method, system and terminal equipment based on principal component analysis. The existing models used for power load forecasting are limited in use scenarios and the forecasting accuracy is not high, which affects the optimal dispatching of the power system and the market. Technical Issues of Operational Efficiency

Method used

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  • Short-term load prediction method and system based on principal component analysis, and terminal equipment
  • Short-term load prediction method and system based on principal component analysis, and terminal equipment
  • Short-term load prediction method and system based on principal component analysis, and terminal equipment

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Embodiment 1

[0041] figure 1It is a flow chart of the steps of the short-term load forecasting method based on principal component analysis described in the embodiment of the present invention, figure 2 It is a flowchart of another step of the short-term load forecasting method based on principal component analysis described in the embodiment of the present invention.

[0042] Such as figure 1 and figure 2 As shown, the embodiment of the present invention provides a short-term load forecasting method based on principal component analysis, including the following steps:

[0043] Step S1. Obtain historical load data and factor indicators related to historical load data from the power system and power meteorological system as sample data, and divide the sample data into training sample data and forecast sample data;

[0044] Step S2. Apply correlation analysis to the load and factor indicators in the training sample data, and filter the factor eigenvalues ​​that affect the load;

[0045...

Embodiment 2

[0080] image 3 It is a frame diagram of the short-term load forecasting system based on principal component analysis described in the embodiment of the present invention.

[0081] Such as image 3 As shown, the embodiment of the present invention also provides a short-term load forecasting system based on principal component analysis, including a data acquisition unit 10, a screening unit 20, an analysis unit 30, a fitting unit 40 and a model building unit 50;

[0082] The data acquisition unit 10 is used to obtain historical load data and factor indicators related to the historical load data from the power system and the power meteorological system as sample data, and divide the sample data into training sample data and forecast sample data;

[0083] The screening unit 20 is used to adopt correlation analysis on the load and factor indicators in the training sample data, and screen the factor eigenvalues ​​that affect the load;

[0084] The analysis unit 30 is used for dim...

Embodiment 3

[0090] An embodiment of the present invention also provides a computer-readable storage medium, which is used to store computer instructions, which when run on a computer, enable the computer to execute the above short-term load forecasting method based on principal component analysis.

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Abstract

The embodiment of the invention relates to a short-term load prediction method and system based on principal component analysis, and terminal equipment. The method comprises the steps of: dividing data obtained from an electric power system and an electric power meteorological system into training sample data and prediction sample data; performing correlation analysis on the training sample data to obtain a factor characteristic value influencing a load; performing dimension reduction processing on each factor characteristic value influencing the load through adoption of a principal componentanalysis method to obtain a principal component characteristic value influencing the load; and using a semi-parameter additive model for superposing the non-linear influences of all principal component characteristic values on the load to establish a load prediction model, so that the influence of interaction between factor characteristic values on load prediction is effectively reduced, the prediction precision of the load prediction model is improved, and the problems of limited usage scenarios and low prediction precision of an existing power load prediction model are solved. The method scientifically and comprehensively extracts factor characteristic value variables influencing the load to provide a more practical reference basis for a power market load predictor to make a scheme.

Description

technical field [0001] The invention relates to the technical field of power system loads, in particular to a short-term load forecasting method, system and terminal equipment based on principal component analysis. Background technique [0002] With the advancement of science, the electric power system promotes a new round of new electric power system reform, and the competitive environment of electric power marketization has initially formed. Therefore, accurate forecasting of electric power load is helpful for rationally arranging dispatching operation and production plan on the electric power system, which is an important way to improve The key to power system security, stability, and reduction of power generation costs. [0003] In order to improve the accuracy of power system load forecasting, experts and scholars at home and abroad have done a lot of research on power system load forecasting. One type of load forecasting scheme is to use the load to be easily affected ...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06Y04S10/50
Inventor 冯歆尧彭泽武杨秋勇谢瀚阳梁盈威苏华权
Owner GUANGDONG POWER GRID CO LTD
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