Abstract Owing to economic and technical reasons, campus buildings in south China were not equipped with air-conditioners (AC) for a long time. With the improvement in teaching conditions in south China, ACs are gradually being installed in teaching buildings, leading to soaring energy consumption. The teaching buildings constitute a large part of the total built-up areas on a campus. Due to the stochastic occupancy in teaching buildings, AC energy use is complicated, which is hard to describe quantitatively. Owing to high coupling relationships among the AC usage, indoor temperature, and energy consumption, it is hard to formulate any strategy on energy-savings management. Based on the data collected from an energy monitoring platform at a typical university in south China, typical patterns were proposed using data mining (DM) approaches. There were 6 AC usage patterns, 4 indoor temperature patterns, and 4 energy consumption patterns, all of which could represent complicated AC energy use. To propose precise energy-savings strategies for random AC usage, the coupling relationships among these components were revealed by multiple machine learning (ML) methods, including the decision tree, AdaBoost, and RandomForest. After that, the energy-saving control rules were formulated. As for short-time AC usage, “Turning off as leaving” is an effective way to save energy. The scales of classrooms need to be considered for usage with medium usage hours, while AC set temperature is a critical control parameter for long-time AC usage. These results provide support for more accurate simulation of energy consumption and efficient energy-saving management in teaching buildings.

中文翻译：

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高校教学楼节能管理空调能耗多维度分析

摘要 由于经济和技术原因，华南地区校园建筑长期以来没有配备空调。随着华南地区教学条件的改善，教学楼逐渐安装空调，导致能耗飙升。教学楼占校园总建筑面积的很大一部分。由于教学楼的随机占用，交流能源使用复杂，难以定量描述。由于空调使用量、室内温度和能耗之间的高度耦合关系，很难制定任何节能管理策略。基于从华南某典型大学能源监测平台收集的数据，使用数据挖掘（DM）方法提出典型模式。共有 6 种 AC 使用模式、4 种室内温度模式和 4 种能源消耗模式，所有这些模式都可以代表复杂的 AC 能源使用。为了针对随机 AC 使用提出精确的节能策略，通过多种机器学习 (ML) 方法，包括决策树、AdaBoost 和 RandomForest，揭示了这些组件之间的耦合关系。之后，制定了节能控制规则。对于短时空调使用，“随走随停”是一种有效的节能方式。中等使用小时数的使用需要考虑教室的尺度，而空调设定温度是长时间使用空调的关键控制参数。这些结果为更准确地模拟教学楼的能耗和高效节能管理提供了支持。