TY - JOUR
T1 - P&ID-based symptom detection for automated energy performance diagnosis in HVAC systems
AU - Taal, Arie
AU - Itard, Laure
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - 4S3F method
KW - BEMS
KW - Energy performance
KW - FDD
KW - HVAC
KW - KPI
KW - Symptom detection
UR - http://www.scopus.com/inward/record.url?scp=85088923629&partnerID=8YFLogxK
U2 - 10.1016/j.autcon.2020.103344
DO - 10.1016/j.autcon.2020.103344
M3 - Article
AN - SCOPUS:85088923629
SN - 0926-5805
VL - 119
JO - Automation in Construction
JF - Automation in Construction
M1 - 103344
ER -