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A smart grid real-time security early warning method and device

A security early warning, smart grid technology, applied in character and pattern recognition, data processing applications, instruments, etc., to achieve the effect of simple calculation, improved online analysis ability, and improved accuracy

Active Publication Date: 2022-02-22
GLOBAL ENERGY INTERCONNECTION RES INST CO LTD +2
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  • Claims
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Problems solved by technology

However, the current distribution network is still a relatively fragile system. Once a large-scale failure or power outage occurs, the consequences are quite serious, even catastrophic. At the same time, the operation of the distribution network will also be affected by the status of the power grid itself and weather conditions. Therefore, in order to improve the security, stability and reliability of the power system, it is necessary to provide a real-time security early warning method for smart grids to provide security early warnings for risks faced in the operation of distribution networks, and to make accurate early warnings for potential failure risks of distribution networks.

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  • A smart grid real-time security early warning method and device
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Embodiment Construction

[0055] The technical solutions provided by the present invention will be described in detail below in the form of specific embodiments in conjunction with the accompanying drawings.

[0056] The technical solution provided by the invention uses a big data real-time computing framework to collect real-time power consumption data of users; uses machine learning knowledge to build a dangerous power consumption model on the historical power consumption data of users, and monitors the power consumption status of users in real time to make the power grid intelligent The batch processing computing framework MapReduce is used to accelerate the construction speed of the prediction model and improve the service quality, and this method is suitable for various batch processing computing engines, and has strong adaptability; the application of machine learning technology monitors the real-time power consumption status of users, and For users with dangerous electricity usage behaviors, humani...

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Abstract

The present invention provides a real-time security early warning method and device for a smart grid. The method includes using preprocessed historical power consumption data as training data to train a classifier model; Electricity data predicts the safety status of power consumption; and issues grid warnings based on the safety status of power consumption. The technical solution provided by the invention is suitable for various big data processing platforms to quickly and effectively analyze and process a large amount of power grid status information, and improves the safety guarantee of the power grid and users.

Description

technical field [0001] The invention belongs to the field of monitoring and forecasting of smart grid operation and maintenance, and in particular relates to a real-time security early warning method and device for smart grids. Background technique [0002] The rapid popularization of smart terminals promotes the continuous development of smart grid in the direction of digitization, informatization and intelligence. The traditional way of manually collecting power grid data is far from meeting the needs of large-scale collection of real-time data in the power grid. An important research direction in today's academia and industry is to improve the online analysis capability of power grid characteristics, realize the overall control of the power grid operation status and optimize the control of system resources, especially the key analysis of customers' electricity consumption behavior and consumption behavior, Realize differentiated services, provide customers with further va...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/06G06Q50/06G06K9/62
CPCG06Q10/0639G06Q50/06G06F18/2411
Inventor 周爱华李敏梁良万钢勇马勇朱力鹏胡斌饶玮杨佩潘森邓松张利平
Owner GLOBAL ENERGY INTERCONNECTION RES INST CO LTD
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