中图分类号：TK01+8；TP301.6
文献标识码：A
DOI：10.19358/j.issn.2096-5133.2022.03.008
引用格式： 代凯旋，曾献辉，詹麟. 基于聚类的双温度优化控制基站空调节能算法[J].信息技术与网络安全，2022，41(3)：44-49.

An energy saving algorithm of base station air conditioning based on clustering for dual temperature optimization control

Abstract：he energy saving of base station air conditioning is a very important part of energy saving and emission reduction in telecom industry. It has important practical significance and research value to find rules and means to improve operation performance from the operation data of air conditioning system through data mining method. Aiming at the problem of energy saving and emission reduction of base station air conditioning, based on the real-time data stream collected by base station, this paper firstly established the air conditioning energy saving model to find the optimal control temperature under the target constraint conditions. Then, aiming at the problem of frequent start and stop times of air conditioning, a dual-temperature control model was proposed to reduce the number of air conditioning starts and further reduce the energy consumption of air conditioning. Finally，in order to deal with outdoor temperature, the change of some uncertain factors such as equipment energy consumption, the segmentation control algorithm of air conditioning temperature was proposed based on clustering algorithm and improved, and the corresponding mode of power was obtained by analyzing the clustering results. The corresponding control strategies were designed for different power modes，finally achieved the effect of base station air conditioning energy consumption reduced by 25%. It provides a reliable basis for enterprise air conditioning energy saving control.

Key words :air conditioning energy saving；dual temperature control；electricity consumption mode；clustering algorithm