Conference Paper

Proceedings of ASim Conference 2024: 5th Asia Conference of IBPSA

Introducing Causality to Symptom Baseline Estimation: A Critical Case Study in Fault Detection of Building Energy Systems

Chujie Lu, Ziao Wang, Martin Mosteiro-Romero, Laure Itard
Department of Architectural Engineering and Technology, TU Delft, the Netherlands

DOI: https://doi.org/10.69357/asim2024.1184
Abstract: Fault detection and diagnosis (FDD) provides several interrelated benefits, including reducing energy waste, enhanced operational efficiency, and maintaining indoor comfort. The initial step in FDD is to detect deviations from normal or expected operation. However, establishing a reliable baseline can be challenging, especially when there is a lack of sufficient system documents or when complex control strategies are involved. This study investigates three feature selection methods for the baseline estimation: expert knowledge-based, correlation-based, and causality-guided, using heating coil valve control estimation as an example. These methods were tested in an office building in the Netherlands. The results show that while the correlation-based method achieved the best estimation, it may lead to false negatives due to features with reverse causality. This study aims to emphasize the necessity of causal analysis in the baseline estimation to achieve reliable FDD in buildings.
Keywords: Feature selection, Causal effect, Fault detection, Air handling unit, Building energy systems
Pages: 1621 - 1628
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