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Power load prediction method and device based on expressway neural network

A power load and neural network technology, which is applied in the field of power load forecasting based on expressway neural network, can solve the problems of single influencing factor and inaccurate power load forecasting, and achieve the effect of high-precision forecasting.

Pending Publication Date: 2021-10-29
STATE GRID SHANDONG ELECTRIC POWER COMPANY WEIFANG POWER SUPPLY +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Therefore, the present invention will solve the technical problem of inaccurate power load forecasting due to the single influencing factor considered in the existing power load forecasting method, thereby providing a power load forecasting method and equipment based on expressway neural network

Method used

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  • Power load prediction method and device based on expressway neural network
  • Power load prediction method and device based on expressway neural network
  • Power load prediction method and device based on expressway neural network

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Embodiment 1

[0064] The embodiment of the present invention provides a method for forecasting power load based on highway neural network, which is based on artificial intelligence highway (Highway) neural network, and is used to predict the short-term power load of the power system, see figure 1 As shown, the method includes:

[0065] Step S12, obtain the power load data and the weather data of the historical time period of the predicted location, and obtain the correlation coefficient of the power load data and the weather data;

[0066] In the embodiment of the present invention, see figure 2 Said step S12 includes:

[0067] Step S121, obtaining a plurality of power load data and corresponding weather data at equal time intervals in the historical time period of the preset location, forming a power load data-weather data pair;

[0068] Step S122, for each power load data-weather pair, adopt the first mathematical model to calculate the correlation coefficient of power load data and we...

Embodiment 2

[0129] The embodiment of the present invention also provides a power load forecasting device based on the expressway neural network, which predicts the power load based on the artificial intelligence expressway neural network, and is used to predict the short-term power load of the power system, see Figure 8 shown, including:

[0130] Data processing module 81, is used for obtaining the power load data and weather data of the historical time period of forecasting place, and obtains the correlation coefficient of power load data and weather data;

[0131] Classification module 82, is used for obtaining characteristic matrix according to described correlation coefficient, and adopts cluster analysis method to classify the operation day of historical load;

[0132] The model building module 83 is used for each type of operation day, with the operation day type, daily power load data and related weather data as input, respectively establishes a corresponding load forecasting mode...

Embodiment 3

[0139] This embodiment provides a kind of electric load forecasting equipment based on expressway neural network, and predicts electric load based on artificial intelligence expressway neural network, such as Figure 9 As shown, the power load forecasting device includes a processor 901 and a memory 902, wherein the processor 901 and the memory 902 can be connected by a bus or in other ways, Figure 9 Take connection via bus as an example.

[0140] The processor 901 can be a central processing unit (Central Processing Unit, CPU) or other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), graphics processing units (Graphics Processing Unit, GPU), embedded neural network processing Neural-network Processing Unit (NPU) or other dedicated deep learning coprocessor, Application Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA) or other programmable logic Chips such as devices, discrete gate o...

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Abstract

The invention discloses a power load prediction method and device based on a highway neural network, and the method comprises the steps: obtaining power load data and weather data of a prediction place in a historical time period, and solving a correlation coefficient of the power load data and the weather data; obtaining a feature matrix according to the correlation coefficient, and classifying the running days of the historical load by adopting a clustering analysis method; for each type of operation days, taking the operation day type, daily power load data and related weather data as input, and respectively establishing a corresponding load prediction model based on an artificial intelligence expressway neural network; and determining the type of the current operation day, and carrying out power load prediction by adopting the load prediction model corresponding to the type of the current operation day. According to the scheme, the accuracy of power load prediction is effectively ensured.

Description

technical field [0001] The invention relates to the technical field of electric load forecasting, in particular to a method and equipment for electric load forecasting based on expressway neural network. Background technique [0002] The power industry is the basic industry of the national economy, and plays a vital role in the stability and stability of the country, the development and construction of society and the people's living and working in peace and contentment. With the development of social economy and the improvement of people's living standards, the construction of smart grid is fully carried out, so massive and multi-dimensional power data are generated in the process of power system operation, supervision and dispatch. In order to achieve efficient and accurate power load forecasting, big data mining technology has become a very important tool method. Considering that a major feature of the power system is that it is impossible to complete a large amount of s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06G06N3/04
CPCG06Q10/04G06Q10/067G06Q50/06G06N3/045
Inventor 王涛朱海南李丰硕陈兵兵刘堃刘传良刘明金峰
Owner STATE GRID SHANDONG ELECTRIC POWER COMPANY WEIFANG POWER SUPPLY
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