5G base station energy-saving implementation method applied to power supply energy-saving cabinet

Abstract

The invention discloses a 5G base station energy-saving implementation method applied to a power supply energy-saving cabinet, and the method comprises the following steps that: a power-saving system issues an instruction, and inquires the position of a current base station and an IMEI number corresponding to NB-IOT power-saving cabinet equipment from a network manager of a core network; and the core network manager provides an information query interface, receives a query command issued by the energy-saving system and returns related data. And the energy-saving system receives the data information returned by the network management system of the core network, and calculates whether the base station needs to switch on and off electricity through a multi-situation awareness decision algorithm. If the calculated result is not lower than the user threshold, maintaining the power-on state, the process is ended. And when the user threshold value is lower than the user threshold value, the power-saving system issues a command of switching the 5G user to the 4G network to the network management system of the core network. And the network manager of the core network migrates the user to the 4G network. And after the migration is finished, the energy-saving system issues and queries dormant equipment information to the network management system of the core network. Maintenance personnel are prevented from being accidentally injured.

Description

technical field [0001] The invention relates to a method for realizing energy saving of a 5G base station applied to a power energy saving cabinet, and belongs to the technical field of communication. Background technique [0002] At present, most 5G base stations use MIMO technology, but the power consumption of a single 5G AAU is several times that of 4G RRU, and the power consumption remains high. According to the latest data analysis, the single system power consumption of 4G is only 1300W, and 5G is 3-4 times that of 4G, calculated based on the current average transfer price of 1.3 yuan / kWh. In 2020, the annual electricity bill for a 4G base station is 20,280 yuan, while the annual electricity bill for a 5G base station will be as high as 54,600 yuan. For example, a communication company will build more than 300,000 5G base stations in 2020, and the cost of optoelectronics will exceed 16 billion yuan. Therefore, the energy-saving technology of 5G base stations is an i...

AI Technical Summary

Problems solved by technology

[0005] 1) Disadvantages of power supply service based on the real-time electricity price of the power grid;

[0006] It does not fundamentally solve the energy consumption problem, but changes from one power supply method to another, the overall power consumption remains unchanged, and does not really bring energy saving and emission reduction to the society;

[0007] 2) The use of wind energy and solar energy storage to suppress the shortcomings of peak power consumption services;

[0008] The problem of energy saving and emission reduction has not been fundamentally solved, and at the same time, problems such as increasing the floor space of the computer room have been introduced, which has increased operating costs;

[0009] 3) Although the patents "Method, Device, Electronic Equipment and Storage Medium for Energy Saving of 5G Base Stations" and "A Method for Energy Saving of 5G Base Stations" have truly achieved the power saving goal, the basis for judging the shutdown of base stations is too simple and crude

In short, considering the energy saving of 5G networks only from the perspective of "number of users", frequent power-on and power-off of 5G devices will cause great damage to related physical devices and affect operating data. The system will generate dirty data with incomplete data information, which will eventually affect For the normal operation of the entire 5G system, it is necessary to find an intelligent shutdown and startup control method that predicts the network situation, and design a shutdown decision system from multiple dimensions and perspectives

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