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Electric power medium and long term load prediction method based on a double-layer regression model

A regression model and load forecasting technology, applied in forecasting, data processing applications, instruments, etc., can solve problems such as weak adaptability to changes, limited forecasting accuracy, and limited algorithm complexity, so as to deepen cognition, improve stability, and improve The effect of forecast accuracy

Pending Publication Date: 2019-04-19
安徽数升数据科技有限公司
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Problems solved by technology

The advantage of the above algorithm is that it is relatively intuitive and easy to use; the disadvantage is that the complexity of the algorithm is limited, the adaptability to changes is weak, and the prediction accuracy is limited

Method used

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  • Electric power medium and long term load prediction method based on a double-layer regression model
  • Electric power medium and long term load prediction method based on a double-layer regression model
  • Electric power medium and long term load prediction method based on a double-layer regression model

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specific Embodiment 1

[0021] Such as figure 1 As shown, the present invention is a method for medium and long-term load forecasting of electric power based on a double-layer regression model, comprising the following steps:

[0022] Step 1. Collect historical data of regional factors by year as sample features; sample features include daily maximum temperature value, daily minimum temperature value, daily average temperature, high temperature duration days, sunshine level, wind speed, rainfall and maximum load value; daily average temperature The calculation is: daily average temperature = (daily maximum temperature + daily minimum temperature) / 2, and the number of high temperature continuous days of the day is the number of days in which the temperature of n consecutive days before the calculation is higher than the current day's temperature;

[0023] Step 2: Divide the regional load in summer into base load and cooling load. By calculating the base load in different years, that is, the average va...

specific Embodiment 2

[0038] Such as figure 2 As shown, the present invention is a method for medium and long-term load forecasting of electric power based on a double-layer regression model, comprising the following steps:

[0039] Step 1. Selectively extract the data sources of the historical data of regional factors by year, and regularly extract the historical data after regular update;

[0040] Step 2: periodically analyze the selectively extracted historical data, and perform data cleaning and feature construction on it; at the same time, perform data cleaning and feature construction on the regularly updated historical data extracted regularly;

[0041] Step 3, integrate and summarize the data and features of the two, and use the vector regression algorithm or random forest regression algorithm to construct a two-layer regression model;

[0042] Step 4: Evaluate and apply the double-layer regression model, and obtain application results; then further optimize and reconstruct the model base...

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Abstract

The invention discloses an electric power medium-and-long-term load prediction method based on a double-layer regression model, and belongs to the technical field of electric power prediction. The method comprises the following steps: collecting regional factor historical data as sample characteristics according to years; dividing District loads in summer into basic loads and cooling loads, and the load ratio is obtained by calculating the basic loads of different years; Constructing a regression model by using the sample characteristics and the load ratio data according to the annual peak-attack summer load data; On the basis of the regression model constructed on the first layer, establishing a regression model on the second layer, further combining regression results of different years,and optimizing meanwhile the prediction precision of the model. By constructing the double-layer regression model based on the multiple regression algorithms, the relevance between the load and the external condition characteristics in the regional peak-to-peak summer period is discovered, so that regional loads under different external conditions in the future are predicted, planning and construction of a regional power grid system are assisted, and the operation stability of a regional power grid is improved.

Description

technical field [0001] The invention belongs to the technical field of electric power forecasting, in particular to a medium and long-term electric power load forecasting method based on a double-layer regression model. Background technique [0002] At present, medium and long-term load forecasting is an important content of power system planning and operation research, and it is also the basis for power system planning and construction. Economical and reliable operation. Most of the current load forecasting algorithms are based on the relationship between power and regional economy, such as elastic coefficient method, output value unit consumption method, etc., or simple mathematical models, such as linear regression model, gray model, etc. The advantage of the above algorithm is that it is relatively intuitive and easy to use; the disadvantage is that the complexity of the algorithm is limited, the adaptability to changes is weak, and the prediction accuracy is limited. ...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06Y04S10/50
Inventor 刘峰
Owner 安徽数升数据科技有限公司
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