BSEG’s Comprehensive Review of Data-Driven FDD Featured in Applied Energy Journal

The esteemed Applied Energy Journal has featured the work of BSEG members. The team includes Research Scientist Zhelun Chen, who served as the lead author, Professor Jin Wen, and PhD Candidate Ojas Pradhan. Collaborating with an international team of around 20 other experts from the International Energy Agency (IEA) Energy in Buildings and Communities Programme (EBC) – ANNEX 81 (Data-Driven Smart Buildings) – Subtask C2 (Automated Fault Detection, Diagnostics and Recommissioning Applications), they collectively provided an in-depth review of the present state-of-the-art data-driven Fault Detection and Diagnostics (FDD) technology, a significant milestone towards accomplishing one of the central tasks of C2. 

Their work reviews three perspectives on data-driven FDD: the general FDD process, the systems studied utilizing this approach, and the evaluation metrics specific to data-driven FDD. In addition to the detailed analysis, their paper identifies and outlines the key challenges that face the future of data-driven FDD, including real-building deployment, performance evaluation and benchmarking, scalability and transferability, interpretability, cyber security and data privacy, user experience, etc. 

This work underscores the dedication of BSEG, with its diverse team of researchers, towards advancing our understanding of FDD, and shaping the direction of future studies in this field.

Link to the publication: A review of data-driven fault detection and diagnostics for building HVAC systems