Load curve convergence optimal inflection point recognition method

A technology of load curve and identification method, applied in the field of identification of optimal inflection point

Inactive Publication Date: 2016-10-05
SHANGHAI MUNICIPAL ELECTRIC POWER CO +1
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Problems solved by technology

However, there are still few researches on the identification of the inflection point of the power load curve. Most of the research focuses on the establishment of the tie-line planning model, the planning and design of the tie-line, operation control and available transmission capacity. Therefore, it is urgent to study a The identification method of the optimal inflection point of load curve convergence

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  • Load curve convergence optimal inflection point recognition method
  • Load curve convergence optimal inflection point recognition method

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Embodiment Construction

[0020] as attached figure 2 As shown, the specific steps of an embodiment of a load curve convergence optimal inflection point identification method proposed by the present invention are as follows:

[0021] (1) Data collection

[0022] Collect historical load data every 15 minutes (a total of 96 data points per day) in the region where the invention is to be implemented.

[0023] (2) Data preprocessing

[0024] The data collected in step S1 is preprocessed, and this step includes the following sub-steps

[0025] 1) Data completion

[0026] For the collected relevant data, it is inevitable that there will be loss and omission. For the missing data, the average value of the historical data at the same time should be used to complete.

[0027] 2) Data correction using wavelet denoising

[0028] For abnormal data, analyze whether it is an outlier point. In order to ensure the correct identification of the overall inflection point of the load curve, the outliers must be pro...

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Abstract

A load curve convergence optimal inflection point recognition method includes the following steps: S1, data collection; S2, data pretreatment including S2-1 data filling and S2-2 data correction through a wavelet de-noising method; S3, achievement of approximate fitting of a load curve based on a data pretreatment technique; and S4, performing mathematical treatment on the obtained fitting daily load curve to determine an optimal inflection point. After pretreatment is performed on the original data through data filling and the wavelet de-noising method, Matlab software is called to perform approximate fitting on polynomial, and in this way, a smooth continuous function format is obtained; an inflection point definition of the mathematics field is applied to the power load curve, the inflection point of the load curve can be rapidly found, and then power dispatching workers can timely determine the present inflection point and can make ready for corresponding dispatching works, and the stability and the reliability of power grid operation can be improved.

Description

technical field [0001] The invention relates to the identification technology of the optimal inflection point, in particular to a method for identifying the optimal inflection point of load curve convergence. Background technique [0002] The load curve is the curve of various power loads in the power system changing with time, and it is the basis for the economic dispatch and system planning of the power system. With the promotion of smart grid dispatching technology in the national power grid, cross-regional and cross-provincial data sharing has been realized, which provides a reliable data basis for the optimal allocation of large-scale resources. It is one of the key links to realize the optimal allocation of cross-regional and cross-provincial resources. Therefore, accurate identification of the inflection point of the power load curve can not only help power dispatchers to prepare for the existence of the inflection point in time, but also provide a certain reference ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/17
Inventor 章渊刘敦楠陆麒亦刘睿智吉立航吴昌昊
Owner SHANGHAI MUNICIPAL ELECTRIC POWER CO
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