Power grid load anomaly prediction method, system and storage medium

A technology of power grid load and forecasting method, applied in forecasting, neural learning methods, information technology support systems, etc., can solve problems such as failure to meet the needs of smart grids, early warning lag, etc., and achieve the effect of realizing abnormal warning and improving accuracy

Pending Publication Date: 2022-02-25
CHINA SOUTHERN POWER GRID DIGITAL GRID RES INST CO LTD
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  • Claims
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Problems solved by technology

This approach can no longer meet the needs of the smart grid
In the traditional solution, through the comparison of real-time data and threshold value, although some abnormal situations can be found, in terms of time, the early warning will lag behind

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  • Power grid load anomaly prediction method, system and storage medium
  • Power grid load anomaly prediction method, system and storage medium
  • Power grid load anomaly prediction method, system and storage medium

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Embodiment Construction

[0035] In order to make the purpose, technical solution and advantages of the application clearer, the technical solution of the application will be clearly and completely described through implementation with reference to the accompanying drawings in the embodiments of the application. Obviously, the described embodiment is the embodiment of the application. Some, but not all, embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

[0036] In the description of the present invention, several means more than one, and multiple means more than two. Greater than, less than, exceeding, etc. are understood as not including the original number, and above, below, within, etc. are understood as including the original number. If the description of the first and second is only for the purpose of distinguishing the technical fea...

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Abstract

The invention discloses a power grid load abnormity prediction method, a system and a storage medium, and relates to a intelligent power grid and artificial intelligence. The method comprises the following steps: obtaining power grid load sequence data; inputting the power grid load sequence data into a pre-trained load anomaly prediction model for prediction to obtain a prediction result of a next time period; the prediction result of the next time period is compared with the early warning value, and whether abnormity occurs or not is judged; wherein the load anomaly prediction model comprises a first sequence model and a second sequence model, and the prediction result of the next time period is determined according to weighting results of the first sequence model and the second sequence model on prediction results of the power grid load sequence data. According to the method, the future load state can be predicted in advance, whether the load abnormity exists or not is judged accordingly, and processing can be carried out in time.

Description

technical field [0001] This application relates to smart grids and artificial intelligence, in particular to a method, system and storage medium for abnormal grid load prediction. Background technique [0002] With the development of power technology, more and more new technologies are integrated into the power grid to form a "smart power grid". The smart grid puts forward higher requirements on the performance of the grid. Such as visualization and real-time of power grid data. [0003] In the past, failures and outages of power grids due to partial overloads occurred from time to time. The previous method was often to first cause a failure and then take measures. Such an approach can no longer meet the needs of the smart grid. In the traditional solution, by comparing the real-time data with the threshold value, although some abnormal situations can be found, the early warning will lag behind in terms of time. Therefore, there is an urgent need for a new method that ca...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06N3/04G06N3/08
CPCG06Q10/04G06Q50/06G06N3/08G06N3/044Y04S10/50
Inventor 余芸明哲萧展辉甘杉甘莹邓丽娟李文俊马赟冯志宏
Owner CHINA SOUTHERN POWER GRID DIGITAL GRID RES INST CO LTD
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