Operational Diagnosis and Data Suitability Assessment Using BMS and Smart-Meter Data in a Multi-Zone University Building

Aggregate building indicators can obscure substantial differences in electrical demand and thermal operation among monitored spaces. This case study examined 89 days of one-minute building management system (BMS) and smart-meter records from a multi-zone university building. Routine data-quality screening was combined with physical interpretation and task requirements to determine how the available channels could be used in the exploratory analyses. The resulting map specifies each channel’s permitted use and any associated monitoring priority. Meter TR1 was selected as the primary monitored-load proxy, whereas Meter G was retained for comparative diagnosis. Primary energy analysis used 59 fully observed TR1 days without imputation or scaling. Sensitivity analyses used all 61 days meeting the 90% and 95% completeness thresholds and reported their energy values as available-minute energy aggregates. Across the 59 fully observed days, weekday energy exceeded weekend energy, and complete 24 h TR1 energy was strongly inversely associated with daily mean outdoor temperature (Spearman ρs=−0.889). Of the 21 monitored spaces, five were warm-biased, four were cold-biased, and 12 were near setpoint. Within the observed winter-to-shoulder-season period, the data supported exploratory load and zone-temperature modeling. The combined assessment established record eligibility and channel use in this incomplete real-world export, and it identified priorities for later monitoring.