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An explanatory parametric model to predict comprehensive post-commissioning building performances

机译:An explanatory parametric model to predict comprehensive post-commissioning building performances

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摘要

Existing building commissioning (EBCx) is a promising approach to save energy and improve indoor environmental quality (IEQ) without sufficient attention yet. However, the uncertainty of building performance post retrofit leads to a low adoption rate of EBCx, as the commissioning outcomes are dependent on various factors and difficult to model. To facilitate decision-making on EBCx, this paper introduces PECCO, a parametric mathematical model enriched with years of commissioning engineering experience to predict comprehensive EBCx outcomes for various types of public buildings, along with a mobile-based tool to automate the prediction process. An 8-min questionnaire is used to collect building parameters regarding general, management, HVAC, smart system, IEQ, electrical, water supply, and building envelope. Then, a mathematical model predicts commissioning outcomes including energy-saving potential, annual cost saving, asset value increase, comfort improvement potential, operation risk, commissioning cost, simple payback period, and difficulty in commissioning, and provides overall commissioning strategies, specific commissioning suggestions, and benchmark figures compared with other buildings. Three case studies suggested that PECCO's prediction on the simple payback period achieved a mean absolute percentage error (MAPE) of 15.47%, which is acceptable and comparable to other related studies. By providing various perspectives of information to building owners and managers, PECCO is helpful to foster the industry to undertake EBCx, leading to a more energy-efficient, low carbon building industry.

著录项

  • 来源
    《Building and environment》 |2022年第4期|108897.1-108897.14|共14页
  • 作者单位

    Tongji Univ, Coll Civil Engn, Room A817,Bldg Coll Civil Engn,1239 Siping Rd, Shanghai 200092, Peoples R China;

    Tongji Univ, Coll Civil Engn, Room A817,Bldg Coll Civil Engn,1239 Siping Rd, Shanghai 200092, Peoples R China|Tongji Univ, Key Lab Performance Evolut & Control Engn Struct, Minist Educ, Shanghai 200092, Peoples R China|Tongji Univ, Shanghai Inst Intellige;

    Harvency Bldg Commissioning Ltd, Shanghai 200023, Peoples R ChinaTongji Univ, Sch Software Engn, Shanghai 200092, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 英语
  • 中图分类
  • 关键词

    Building commissioning; Energy conservation; Expert system; Prediction model;

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