Energy Optimization in Research Infrastructure: A Data-Driven Analysis of the CEK Building

Abstract

This thesis presents a bottom-up energy audit of the Esther Koplowitz Centre (CEK) building at IDIBAPS, Barcelona, to guide targeted energy-saving actions. Due to the absence of permanent metering, this study combined a detailed equipment inventory, short-term monitoring campaigns, and statistical modeling of hourly electricity data from 2023–2024. The calibrated model explains 97% of measured weekly demand, with a relative error of 3%, and captures seasonal variation with a Mean Absolute Percentage Error (MAPE) of 6.8%. Disaggregation reveals a concentrated energy profile, with HVAC systems responsible for ~52% of annual use, followed by laboratory equipment (~36%) and the Data Processing Center (CPD; ~9%). Regression analysis further shows that outdoor temperature and daily occupancy explain 83% of day-to-day energy variability, with summer temperatures strongly influencing seasonal peaks. Three high-impact interventions emerge, ranked by estimated savings: (i) submetering and recommissioning HVAC subsystems; (ii) raising set-points of ultra-low temperature (ULT) freezers from -80 °C to -70 °C; and (iii) increasing the CPD cooling set-point from 24 °C to 26 °C. Together, these measures would cut consumption by ≈ 0.43 GWh per year (about 8.1 MWh per week)—11 % of today’s 3.87 GWh annual load. Despite limited metering infrastructure, this approach demonstrates how a datainformed audit can reliably uncover savings opportunities and provide a scalable audit framework applicable to comparable biomedical research infrastructures.