Base station energy consumption optimization method and system based on decision tree

Abstract

The invention provides a base station energy consumption optimization method based on a decision tree. The base station energy consumption optimization method comprises the following steps: obtaining base station energy consumption parameter information, and monitoring the working condition of the base station in a real-time manner according to the base station energy consumption parameter information, wherein the base station energy consumption parameter information comprises a base station type and electricity consumption of the base station; calculating average electricity consumption, maximum electricity consumption and minimum electricity consumption of each base station per unit time according to the base station energy consumption parameter information; using the average electricity consumption and actual electricity consumption as points, and using the distance between the two points in the space to measure the electricity consumption approximation ratio of each base station, wherein when the electricity consumption approximation ratio of one base station exceeds an approximation ratio standard threshold of similar base stations, said base station is an abnormal base station; and setting an optimization measure and optimization measure weight factors, creating the decision tree accordingly, and using the decision tree to evaluate the abnormal base station and output an optimization measure evaluation report to guide a user to optimize the base station according to the optimization measure evaluation report. The decision tree is used for optimizing the base station according to a detection result, and the data collection is comprehensive.

Description

technical field [0001] The present invention relates to the field of power systems, in particular to a method and system for optimizing energy consumption of a base station based on a decision tree. Background technique [0002] Existing smart meters use communication interfaces to transmit power consumption readings and data such as current, voltage, temperature, and humidity. This technology can transmit readings and other related data, but it cannot tell whether the base station has excessive or low power consumption, skipping meters, etc. Indication of abnormal failure. [0003] In the prior art, mathematical modeling is used to evaluate equipment, which is mainly introduced to use temperature, power consumption measurement, and energy compensation as the main data modeling direction, and lacks corresponding feedback and optimization mechanisms. This mathematical model is based on the power consumption of the base station changing with the time period, and the power con...

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to provide a base station energy consumption optimization method based on a decision tree that can timely and efficiently optimize high energy consumption base stations, so as to solve abnormal energy consumption of base stations, untimely maintenance, poor dynamic continuity, The problem of poor real-time performance

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