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Data mining based framework to identify rule based operation strategies for buildings with power metering system

机译:基于数据挖掘的框架,用于识别具有电能计量系统的建筑物的基于规则的操作策略

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摘要

Operation strategies influence the building energy efficiency. In order to enhance the building energy efficiency, it's necessary to adopt proper operation strategies on building equipment. Thus, the identification of existing operation strategies is necessary for the improvement of operation strategies. A data mining (DM) based framework is proposed in this paper to automatical y identify the building operation strategies. The framework includes classification and regression tree (CART), and weighted association rule mining (WARM) method, targeting at three types of rule based control strategies: on/off control, sequencing control (for equipment of the same type), and coordinated control (for equipment of different types). The performance of this framework is validated with power metering system data and manual identification results based on on-site survey of three buildings in Shanghai. The validation results suggest that the proposed framework is capable of identifying building operation strategies accurately and automatical y. Implemented on the original software named BOSA (Building Operation Strategy Analysis), this framework is promising to be used in engineering field to enhance the efficiency of building operation strategy identification work.
机译:运营策略会影响建筑的能效。为了提高建筑物的能源效率,必须在建筑物设备上采取适当的操作策略。因此,识别现有的操作策略对于改进操作策略是必要的。本文提出了一种基于数据挖掘(DM)的框架,以自动识别建筑物的运行策略。该框架包括分类和回归树(CART)和加权关联规则挖掘(WARM)方法,针对三种基于规则的控制策略:开/关控制,顺序控制(用于相同类型的设备)和协调控制(用于不同类型的设备)。该框架的性能通过电力计量系统数据和基于上海三座建筑物的现场调查的人工识别结果进行了验证。验证结果表明,所提出的框架能够准确,自动地识别建筑物的运行策略。该框架在名为BOSA(建筑运营策略分析)的原始软件上实施,有望在工程领域中使用,以提高建筑运营策略识别工作的效率。

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  • 来源
    《建筑模拟(英文版)》 |2019年第2期|195-205|共11页
  • 作者单位

    School of Mechanical Engineering, Tongji University, Shanghai, China;

    School of Mechanical Engineering, Tongji University, Shanghai, China;

    School of Mechanical Engineering, Tongji University, Shanghai, China;

    School of Mechanical Engineering, Tongji University, Shanghai, China;

    School of Mechanical Engineering, Tongji University, Shanghai, China;

    School of Mechanical Engineering, Tongji University, Shanghai, China;

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  • 入库时间 2022-08-19 04:29:07
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