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Power load prediction method and system

A technology of power load and forecasting method, applied in the field of power load forecasting method and system, which can solve the problems of increasing the difficulty of short-term load forecasting, and achieve the effect of improving distribution efficiency and accuracy

Pending Publication Date: 2021-06-22
XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY
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Problems solved by technology

[0003] However, the power load data generally has a certain periodicity, such as weekly periodicity, monthly periodicity and annual periodicity. certain randomness
The uncertainty caused by such randomness significantly increases the difficulty of short-term load forecasting

Method used

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  • Power load prediction method and system
  • Power load prediction method and system

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Experimental program
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Embodiment Construction

[0068] The present invention is further described below in conjunction with accompanying drawing:

[0069] refer to figure 1 , the present invention provides a power load forecasting method optimized based on the adaptive simulated annealing particle swarm optimization algorithm, including extracting the historical data of the power load from the database, screening the influencing parameters of the historical data corresponding to the power load, and dividing the training set and test set;

[0070] Using support vector machine and particle swarm optimization algorithm to establish a power load forecasting model, the influence parameters corresponding to the historical data of power load in the training set are used as input variables, input into the power load forecasting model for training, and after the training is completed, the training results are passed through the test set. test;

[0071] Power load forecasting is one of the important tasks of the power sector. Accur...

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Abstract

The invention discloses a power load prediction method and system. The method comprises the following steps: primarily selecting influence factors influencing the power load through preliminary analysis; obtaining long-term historical data of the influence factors from a historical database, removing redundant related variables and variables which are not greatly correlated with the power load by means of mutual information correlation analysis, and screening out input variables of a power load prediction model; on the basis, a support vector machine and an adaptive simulated annealing particle swarm algorithm being adopted to establish a prediction model of the power load, and real-time prediction of the future power load being realized. According to the invention, the power plant can be effectively and timely guided to reasonably distribute power, and the power transmission efficiency is improved.

Description

technical field [0001] The invention relates to the field of electric load forecasting, in particular to an electric load forecasting method and system. Background technique [0002] Power load forecasting is the basis of power system operation and planning. Accurate load forecasting can ensure the safe and stable operation of the power system, reduce power generation costs, and improve economic benefits. With the development of the power industry and the increase of distributed energy sources, short-term load forecasting is becoming more and more important. Considering the nonlinearity, heteroscedasticity, and non-stationary characteristics of power load data, the difficulty of short-term load forecasting also increases significantly. [0003] However, the power load data generally has a certain periodicity, such as weekly periodicity, monthly periodicity and annual periodicity. A certain amount of randomness. The uncertainty caused by such randomness significantly incre...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06Q10/06G06N3/00
CPCG06Q10/04G06Q50/06G06Q10/067G06N3/006Y04S10/50Y02P90/82Y02E40/70
Inventor 边根庆刘陆
Owner XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY
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