Adding Contextuality to Building Analysis: Development and Implementation of Operational HVAC Performance Assessments

Research output: PhD thesis

Abstract

Building management systems have evolved over the years as computational power has increased, data storage has gotten cheaper, and buildings have increased their level of monitoring. This has increased the potential of using their data for more purposes than simple monitoring, such as fault detection or advanced building assessments. These improvements have, though, not fully found their way into the industry yet, with many building management systems still only having the classic monitoring capacity.
This thesis has, therefore, investigated the barriers and drivers related to academia and the building industry through an extensive literature study and interviews with experts from the industry to determine how the implementation of the advanced methods can be furthered from the academic side.
The results from these initial studies led to the development of KPIs, assessments, and fault detection methods centered around the concept of contextuality, which showed promising results in enhancing our understanding of the building’s and HVAC system’s performance.
Original languageEnglish
Supervisors
  • Jensen, Rasmus Lund, Principal supervisor
  • Heiselberg, Per Kvols, Co-supervisor
Publisher
Electronic ISBNs978-87-85239-56-3
Publication statusPublished - 2024

Keywords

  • HVAC
  • Fault Detection
  • Contextual Key Performance Indicators
  • Building Performance Analysis
  • Building Management System
  • Machine Learning
  • Air Handling Unit

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