Temperature based power load data long-term prediction method

A technology of power load and forecasting method, which is applied in the field of data processing and can solve problems such as temperature, information loss, and forecast effect decline that are not considered.

Active Publication Date: 2015-07-22
UNIV OF SCI & TECH OF CHINA
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Problems solved by technology

These methods have indeed achieved good results, but they are often only for short-term load forecasting, and as time goes by, the forecasting effect declines significantly
On the other hand, the combined processing of raw data and mod

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  • Temperature based power load data long-term prediction method
  • Temperature based power load data long-term prediction method
  • Temperature based power load data long-term prediction method

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Embodiment Construction

[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some 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.

[0020] An embodiment of the present invention provides a temperature-based long-term prediction method for electric load data. Such as figure 1 As shown, the method mainly includes the following steps:

[0021] Step 11. Obtain the power load data and the daily average temperature at the collection point within a certain period of time.

[0022] Step 12. Using the daily average temperature as the descriptive index of the power load data, based on ...

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Abstract

The invention discloses a temperature based power load data long-term prediction method. The method comprises the following steps: acquiring power load data and daily mean temperature of collection time points in a certain time interval; and with the daily mean temperature as a description index of power load data and based on the acquired power load data and a regression method based marginal increment model, predicting the daily power load value at a certain daily mean temperature one day. According to the method disclosed by the invention, temperature is used as the description index of power load data, so that the prediction of the power load data is effectively related to temperature, and moreover, the primitiveness of data is not damaged in processing. In addition, aiming at the defect of data set deficiency, a marginal increment is set for making up for the deficiency; in a traditional method in which load is converted into a time sequence to be processed, medium and long-term prediction cannot be realized; and the technical scheme disclosed by the invention can well solve the problem.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a temperature-based long-term prediction method for electric load data. Background technique [0002] At present, there are many methods for power load forecasting. Some are based on forecasting models such as artificial networks and support vector machines to fit the load curve, and some are based on the typical periodic time series characteristics of the load, using models such as ARIMA to predict. These methods have indeed achieved good results, but they are often only for short-term load forecasting, and as time goes by, the forecasting effect declines significantly. On the other hand, the combination of raw data and models will inevitably result in loss of information. [0003] In these traditional methods, load is only regarded as an application object of time series, and factors such as temperature which are closely related to it are not considered. Contents of...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
Inventor 董雨肖坚红赵永红李春生徐刚陈驰李家丽麦鸿坤张泽宇
Owner UNIV OF SCI & TECH OF CHINA
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