Identification method and system for power load prediction key factors

A key factor, power load technology, applied in forecasting, character and pattern recognition, instruments, etc., can solve problems such as low accuracy and large error, and achieve the effect of improving accuracy

Pending Publication Date: 2022-03-04
SHENZHEN POWER SUPPLY BUREAU
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0009] The purpose of the present invention is to propose a method and system for identifying key factors in power load forecasting, and to solv

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  • Identification method and system for power load prediction key factors
  • Identification method and system for power load prediction key factors
  • Identification method and system for power load prediction key factors

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Embodiment Construction

[0055] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0056] like figure 1 As shown, it is a schematic diagram of an embodiment of a method for identifying key factors in power load forecasting provided by the present invention. In this embodiment, the method includes:

[0057] Obtain environmental variable data; wherein, the environmental variables at least include maximum temperature data, minimum temperature data, average temperature data, maximum wind speed data, minimum wind speed data, average wind speed data, sunshine intensity data, average humidity data, weekly date data, Holiday type data; that is, select 10 indicators such as maximum temperature, minimum temperature, average temperature, maximum wind speed, minimum wind speed, average wind speed, sunshine intensity, average humidity, day of the week, and ...

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Abstract

The invention provides a power load prediction key factor identification method and system, and the method comprises the steps: obtaining environment variable data; performing normalization processing on the environment variable data according to a preset normalization rule to obtain an environment variable set; and inputting the environment variable set as an input quantity into a pre-trained related factor identification model to obtain a power load prediction key factor. The method has the capability of dynamically identifying the key related factors in different scenes according to the boundary data, so that the dynamic identification of the key related factors is realized, and the power load prediction accuracy is improved. And according to the external environment change, dynamically selecting a related factor which has the closest relationship with the power load, and taking the related factor as an input quantity of a related factor prediction algorithm, thereby realizing dynamic prediction analysis according to the external environment change.

Description

technical field [0001] The invention relates to the technical field of electric load forecasting, in particular to an identification method and system for key factors of electric load forecasting. Background technique [0002] Power load forecasting is an important basis for power grid dispatch optimization, and has a direct impact on operations such as operation mode arrangement and generation plan preparation. In recent years, with the continuous deepening of power market reform, market members have been paying more and more attention to the rationality of power grid dispatching and operation planning, and power load forecasting is the focus of attention. [0003] Among the traditional power load forecasting methods, forecasting methods based on weather forecasting and other related factors are important methods for power load forecasting. Temperature, wind, sunshine, precipitation and other meteorological factors, holiday factors, economic factors, etc. will all have an ...

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06G06K9/62
CPCG06Q10/04G06Q10/067G06Q10/06393G06Q50/06G06F18/214
Inventor 李江南刘傲程韧俐祝宇翔史军张炀车诒颖
Owner SHENZHEN POWER SUPPLY BUREAU
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