Power grid load forecasting method and system based on artificial intelligence

A power grid load and artificial intelligence technology, applied in the field of artificial intelligence, can solve problems such as the inability to capture changes in dynamic consumption patterns and the inability to evaluate the uncertainty of load demand, and achieve the effect of reducing errors and improving accuracy

Active Publication Date: 2022-03-29
XINFENGGUANG ELECTRONICS TECH CO LTD
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  • Abstract
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AI Technical Summary

Problems solved by technology

However, these techniques cannot assess the inherent uncertainties in load demand and capture changes in dynamic consumption patterns

Method used

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  • Power grid load forecasting method and system based on artificial intelligence

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Embodiment Construction

[0039] In order to further explain the technical means and effects of the present invention to achieve the intended purpose of the invention, the specific implementation methods of the artificial intelligence-based power grid load forecasting method and system proposed according to the present invention will be described below in conjunction with the accompanying drawings and preferred embodiments , structure, feature and effect thereof are described in detail as follows. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0040] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field of the invention.

[0041] The specific scheme of the artificial intelli...

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Abstract

The invention relates to the technical field of artificial intelligence, in particular to an artificial intelligence-based grid load forecasting method and system. The method includes the following steps: collecting historical load data of the power grid, and performing periodic correlation analysis on the historical load data in different periods; according to the results of the correlation analysis, using a predictive neural network to obtain the predicted load sequence of the target day in different periods ; Select the forecasted load sequence of the same target day under different periods, decompose it to fluctuate, obtain the corresponding trend component, period component and random component, and then form a feature sequence, and use the feature sequence to obtain the accurate forecast load of the target day. The embodiment of the present invention predicts the load of the power grid through the mutual correlation of the loads of the power grid in different periods, and can learn the rules of different periods, reduce errors as much as possible, and improve the accuracy of load forecasting.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to an artificial intelligence-based grid load forecasting method and system. Background technique [0002] Load forecasting plays a vital role in grid operation planning and management in modern energy systems, often referred to as smart grid (SG) systems. With the advent of smart meters and advanced metering infrastructure (AMI) in SG, the two-way flow of energy and data has increased significantly. Therefore, many data analysis applications have recently emerged, such as load forecasting in SG systems. Load forecasting is crucial for many energy management tasks in power grids, such as generation capacity scheduling, supply and demand planning, and minimization of energy transaction costs. In recent years, with the continuous development of power systems and smart grids, the importance of load forecasting has expanded significantly. Additionally, accurate load f...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/00G06Q10/04G06Q50/06G06N3/04G06N3/08H02J3/00
CPCG06Q10/04G06Q50/06G06N3/049G06N3/08H02J3/003G06N3/044G06N3/045Y04S10/50
Inventor 张长元陈天雁陈敏刘丽敏蔡宝柱周鑫田杰朱英华
Owner XINFENGGUANG ELECTRONICS TECH CO LTD
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