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Medium-and-long term typical daily load curve prediction method based on function type nonparametric regression

A non-parametric regression and daily load technology, applied in forecasting, data processing applications, instruments, etc., can solve problems such as rough forecasting results and large errors

Active Publication Date: 2014-08-13
WUHAN UNIV
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

The prediction result of this method is relatively rough and the error is large

Method used

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  • Medium-and-long term typical daily load curve prediction method based on function type nonparametric regression
  • Medium-and-long term typical daily load curve prediction method based on function type nonparametric regression
  • Medium-and-long term typical daily load curve prediction method based on function type nonparametric regression

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Embodiment

[0049] 1. The technical solution of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0050] The present invention comprises the following steps:

[0051] Step 1: Based on the maximum load value in each historical typical daily load curve as the reference value, normalize each historical typical daily load curve; based on the following formula:

[0052] S * (t m ) = S(t m ) / S max m=1,2,...,P,

[0053] Among them, S(t m ) represents the load value at each moment of the typical daily load curve; S max Indicates the maximum load value of a typical daily load curve; S * (t m ) represents the value of the typical daily load curve at each time after normalization processing, and P represents the number of time;

[0054] Step 2: Use the semi-metric calculation method based on functional principal component analysis to calculate the semi-metric between the historical curve samples after normalization proces...

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Abstract

The invention discloses a medium-and-long term typical daily load curve prediction method based on function type nonparametric regression which comprises the following steps: according to an existing historical daily load curve, based on a functional data analysis theory and a nonparametric kernel density estimation method, establishing a functional nonparametric regression prediction model; and by considering a daily load factor and a minimum load factor of a typical day to be predicted, establishing a quadratic programming model to correct a prediction curve of the functional nonparametric regression prediction model, and finally, obtaining the prediction curve meeting a load characteristic index requirement of the typical day to be predicted. A simulation example based on typical daily load data of a certain provincial power grid in China and PJM (Pennsylvania-New Jersey-Maryland) electric power company in America proves that the method disclosed by the invention is simple and practical, and is accurate in prediction result. The method has a god popularization value and application prospect.

Description

technical field [0001] The invention belongs to the field of power system load forecasting, and relates to a medium- and long-term typical daily load curve forecasting method based on a functional non-parametric regression model. Background technique [0002] The medium and long-term typical daily load curve prediction refers to the prediction of the typical daily load time series curve of the month, season and year from 1 to 10 years. It is of great significance to the optimization of power supply and power grid. The basis for the benefits of peak shift regulation in interconnected systems. [0003] Different from the short-term daily load curve forecast, the medium- and long-term typical daily load curve forecast has the following characteristics: the typical daily load curves in the same month in different years have similar shapes and similar changing rules; typical daily load characteristic indicators, such as daily load rate and minimum load rate can Reflect the shape...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCY04S10/54Y04S10/50
Inventor 徐箭许梁孙涛黄磊
Owner WUHAN UNIV
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