| 摘要: |
| 本文提出了一种地铁站环控系统用能诊断方法，通过数据挖掘技术建立评价模型来评价地铁环控系统的用能特性。首先，通过相关性分析，确定影响地铁环控系统能耗的关键变量：室外温度、客流量；其次，根据所选取的关键变量，采用决策树划分不同的用能模式，进而根据各个模式建立相应的用能基准；最后，根据不同模式的用能基准对地铁环控系统实际运行数据进行用能诊断。诊断结果表明：环境和客流的变化会引起用能水平的波动，但仍然贴近用能基准。该用能诊断方法能够诊断地铁站用能、识别异常用能模式和识别低能耗的用能模式，有助于地铁站运营漏洞、故障排查和环控模式优化，为单个地铁站的节能工作提供理论依据和实际参考。 |
| 关键词: 数据挖掘 地铁环控系统 用能诊断 能耗等级 节能优化 |
| DOI： |
| 投稿时间：2017-05-04
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| 基金项目:国家自然科学基金（51576074&51328602）资助项目。 |
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| Energy Consumption Diagnosis Method based on Data Mining Technology in HVAC System in Subway Stations |
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Liu Jiahui1, Long Jing2, Pan Zhigang2, Chen Huanxin1, Liu Jiangyan1, Huang Ronggeng1, Li Zhengfei1
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| (1.Department of Refrigeration & Cryogenics, Huazhong University of Science and Technology;2.Guangzhou Metro Corporation) |
| Abstract: |
| This paper proposes an energy consumption diagnosis method and establishes an evaluation model based on data mining technology for evaluating the energy utilization of HVAC systems used in subway stations. First, through a correlation analysis, the key variables that influence the energy consumption of the subway’s HVAC system are determined, namely, the outdoor temperature and passenger flows. Then, according to the selected key variables, different energy utilization modes are generated using a decision tree, after which an energy benchmark is established on the basis of the energy consumption models. Finally, an energy consumption diagnosis method based on the energy benchmark of different energy utilization modes is applied to actual data of an HVAC system. The results of energy consumption diagnosis show that the energy levels can be influenced by the changes in the environment and passenger flow, but still conform to the energy benchmark. This energy consumption diagnosis method can diagnose the conditions of energy utilization and recognize modes of abnormal or low energy consumption, which can optimize energy utilization and provide a theoretical basis and practical reference for energy savings at a single subway station. |
| Key words: data mining HVAC system in subway stations energy consumption diagnosis energy rating optimization and energy saving |
