Power consumption management method and system based on MEC edge intelligent gateway

Abstract

The invention discloses a power consumption management method and system based on an MEC edge intelligent gateway, and the method comprises the steps: carrying out the global management of basic configuration information through a cloud center, collecting historical power consumption data in a classified manner through an intelligent instrument, transmitting the historical power consumption data to the MEC edge intelligent gateway through a base station, and preprocessing original data through an end module; analyzing and training user power utilization data according to the AI module to forma user power utilization business demand model, and encrypting and uploading a trained model gradient parameter data surface; analyzing the encryption model gradient of the edge gateway and aggregating and training a plurality of models to form a joint model, and backing up and issuing gateway model gradient parameters; and updating the model parameters and information reserved by other data, andsending back power utilization management decision information to the corresponding user side according to the actual situation. According to the method and system, the computing power of one side ofedge computing is improved, and the requirement of a user for protecting private data of power utilization of the user is met in the contemporary society of mass data interaction.

Description

technical field [0001] The present invention relates to the technical field of edge computing of electric power internet of things, in particular to a method and system for managing power consumption based on an MEC edge intelligent gateway. Background technique [0002] At present, the social power technology is becoming more and more mature, the country's power generation has repeatedly hit new highs, the area covered by social power consumption is becoming wider and wider, and the groups of power users are becoming more and more complicated, including individual users, government agencies and enterprise factories. Types of. Such a large-scale power consumption will inevitably bring about many safety problems, such as the occurrence of electrical fires caused by overloaded power consumption by users, the leakage of electricity that causes many people to be electrocuted and injured every year, and the improper use of power resources leads to high power costs, etc. It can b...

AI Technical Summary

Problems solved by technology

Such a large-scale power consumption will inevitably bring about many safety problems, such as the occurrence of electrical fires caused by overloaded power consumption by users, the leakage of electricity that causes many people to be electrocuted and injured every year, and the improper use of power resources leading to high power costs, etc.

It can be seen that there is an urgent need for more complete technology to manage electricity consumption in China. The traditional electricity management method is managed manually, but the labor cost is high and the management is difficult. There is also intelligent monitoring locally, but it is not suitable. Large-scale user management. For this reason, people think of uploading terminal data to the cloud platform for user power consumption management, which has a better effect than before. However, with the continuous deepening of the power Internet of Things in the industry, the number of terminal equipment The rapid increase, the operation of each terminal will inevitably generate some data, so the data generated by a large number of terminals must be massive, and too much data will inevitably occupy a large amount of bandwidth and high delay, which will make the performance of cloud computing encounter bottlenecks. In this context, how to analyze massive user electricity consumption data and obtain effective information from it has become extremely challenging

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