P&ID-based symptom detection for automated energy performance diagnosis in HVAC systems

Arie Taal*, Laure Itard

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)


Current symptom detection methods for energy diagnosis in heating, ventilation and air conditioning (HVAC) systems are not standardised and not consistent with HVAC process and instrumentation diagrams (P&IDs) as used by engineers to design and operate these systems, leading to a very limited application of energy performance diagnosis systems in practice. This paper proposes detection methods to overcome these issues, based on the 4S3F (four types of symptom and three types of faults) framework. A set of generic symptoms divided into three categories (balance, energy performance and operational state symptoms) is discussed and related performance indicators are developed, using efficiencies, seasonal performance factors, capacities, and control and design-based operational indicators. The symptom detection method was applied successfully to the HVAC system of the building of The Hague University of Applied Sciences. Detection results on an annual, monthly and daily basis are discussed and compared.

Original languageEnglish
Article number103344
Number of pages20
JournalAutomation in Construction
Publication statusPublished - 2020


  • 4S3F method
  • BEMS
  • Energy performance
  • FDD
  • HVAC
  • KPI
  • Symptom detection


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