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Power consumer electricity consumption behavior prediction method and prediction system

A technology of power users and prediction methods, which is applied in the field of electric power, can solve the problems of not providing power user behavior prediction methods and prediction systems, and achieve effective and accurate prediction results, good real-time prediction, and reduced field strength errors

Pending Publication Date: 2020-05-29
GUIZHOU POWER GRID CO LTD
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the prior art does not provide an effective and accurate power consumption behavior prediction method and prediction system for power users in the power system, that is, the load forecasting problem.

Method used

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  • Power consumer electricity consumption behavior prediction method and prediction system
  • Power consumer electricity consumption behavior prediction method and prediction system
  • Power consumer electricity consumption behavior prediction method and prediction system

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Experimental program
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Effect test

Embodiment 1

[0027] refer to figure 1 As shown, the power user behavior prediction method provided in this embodiment includes the following steps:

[0028] 101. Obtain the required user's historical power consumption data and the historical temperature data of the user's location; wherein, the user's historical power consumption data can be obtained from the power grid system where the user is located, and the historical temperature data can be obtained from the meteorological bureau system where the user is located Get it.

[0029] 102. Construct a temperature psychological field model based on the acquired user historical electricity consumption data and historical temperature data;

[0030] 103. Use the acquired user historical electricity consumption data and historical temperature data as the input vector of the SVM support vector machine, and calculate the current user's predicted initial value of electricity consumption based on the SVM regression estimation method

[0031] SVM...

Embodiment 2

[0066] refer to Figure 4 As shown, the power user behavior prediction system provided in this embodiment includes:

[0067] The data collector 401 is used to collect the required user's historical electricity consumption data and the historical temperature data of the user's location; in this embodiment, the data collector can use existing data grabbing tools, such as Silicon Valley data tools GrowingIO, then captures historical power consumption data and historical temperature data of the user's location from the power grid system where the user is located and the Meteorological Bureau system; after capturing relevant data, transmit the relevant data to the first data processor 402;

[0068] The first data processor 402 is used to calculate and process the user's historical power consumption data and historical air temperature data transmitted by the data collector 401 to generate a temperature psychological field model; The quantity data and historical temperature data are...

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Abstract

The invention discloses a power consumer electricity consumption behavior prediction method and prediction system. The method comprises the following steps: acquiring historical power consumption dataof a required consumer and historical air temperature data of a place where the consumer is located; constructing an air temperature psychological field model according to the acquired historical electricity consumption data and historical air temperature data of the user; taking the obtained historical electricity consumption data and historical air temperature data of the user as input vectorsof an SVM support vector machine, obtaining a predicted electricity consumption initial value of the current user through calculation, and calculating the current predicted air temperature psychological field intensity according to the predicted electricity consumption initial value in combination with an air temperature psychological field model and a multi-scene set method; standardizing the airtemperature psychological field intensity in the prediction time period to obtain a correction coefficient for correcting and predicting an initial power utilization value based on an air temperaturepsychological field theory; and calculating a final prediction value of the user power consumption behavior by combining the user power consumption initial value and the correction coefficient. The method can effectively ensure the normal operation of the power network and reduce the economic loss of a power company.

Description

technical field [0001] The invention relates to the field of electric power technology, in particular to a method and system for predicting power consumption behavior of power users. Background technique [0002] The power consumption behavior of power users refers to the power consumption activities of users as the main body of power consumption under the influence of external environmental factors, which is mainly reflected in the changes in the power consumption load of users. By effectively grasping the power consumption behavior of power users, it is possible to provide users with better power services, reduce the power supply load pressure of power supply units, and avoid abnormal power consumption behaviors leading to wrong judgments on future power demand, which will cause serious economic losses to power companies. loss, affecting the normal operation of the power network. Therefore, how to effectively predict the user's electricity consumption behavior is very imp...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06K9/62
CPCG06Q10/04G06Q50/06G06F18/2411
Inventor 姚璐宁楠邵倩文谢威吴小康廖清阳尚晓霞宗志亚王安安赛
Owner GUIZHOU POWER GRID CO LTD
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