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Power load prediction method of improved gray model based on particle swarm optimization

A technology of particle swarm optimization and gray model, applied in prediction, electrical digital data processing, instruments, etc., can solve problems such as poor anti-interference ability and large jump error, and achieve the effect of improving accuracy and reducing error

Active Publication Date: 2021-05-04
NANJING UNIV OF POSTS & TELECOMM +1
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Problems solved by technology

[0006] The purpose of the present invention is to provide a power load forecasting method based on an improved gray model based on particle swarm optimization for the problems that the original gray forecasting model GM(1,1) in the prior art has large jump errors and poor anti-interference ability

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  • Power load prediction method of improved gray model based on particle swarm optimization
  • Power load prediction method of improved gray model based on particle swarm optimization
  • Power load prediction method of improved gray model based on particle swarm optimization

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[0075] The technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0076] In this embodiment, the load data of a certain city from 2001 to 2011 is taken as the research object, and the load data are shown in Table 1:

[0077] Table 1 2001-2011 power grid load data of a city

[0078] serial number year (year) Electricity consumption (100 million KWh) 1 2001 532.05 2 2002 641.35 3 2003 643.4 4 2004 840.36 5 2005 857.02 6 2006 942.59 7 2007 1177.51 8 2008 1213.39 9 2009 1324.61 10 ...

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Abstract

The invention discloses a power load prediction method of an improved gray model based on particle swarm optimization, belongs to the technical field of power system load prediction, and aims at solving the problems that an existing gray prediction model is large in fluctuation along with load change and poor in prediction effect, the method comprises steps of utilizing agray prediction model DTGM (1, 1) based on data transformation, predicting a load value of an (n + 1) year under the condition of obtaining load data of previous n years, solving optimal values of residual state interval parameters lambda1, lambda2,... lambdan through a particle swarm optimization (PSO) algorithm, obtaining an optimal residual correction value to correct an original prediction model, and finally obtaining a corrected prediction value; the corrected DTGM (1, 1) has higher prediction precision, and the defects of a traditional gray prediction model are overcome.

Description

technical field [0001] The invention belongs to the technical field of power system load forecasting, in particular to a power load forecasting method based on an improved gray model of particle swarm optimization. Background technique [0002] With the rapid development of science and technology and economy in our country, electric energy has become an indispensable energy in people's daily life. With the improvement of living standards, users have higher and higher requirements for power supply reliability. However, since electric energy is a secondary energy source, it cannot be stored in large quantities. In order to improve the reliability of power supply and ensure the balance between power supply and power consumption, it is necessary to understand the power consumption situation, that is, the characteristics of the load, and reasonably predict and grasp the load. To provide accurate suggestions for power scheduling to ensure the reliability of power supply and provid...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06F16/2458G06Q50/06
CPCG06Q10/04G06Q50/06G06F16/2474Y04S10/50
Inventor 窦春霞李想岳东张智俊丁孝华李延满
Owner NANJING UNIV OF POSTS & TELECOMM
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