Comparative Analysis of Energy Consumption in a University Building Using Traditional and Smart Metering: A Case Study with Uncertainty Quantification for Demand Response

This article evaluates the relevance of Advanced Metering Infrastructure (AMI) as an essential tool for understanding real consumption profiles, particularly in mixed-use buildings with high operational variability. The study focuses on Building 225 Rogelio Salmona at the Bogotá campus of the National University of Colombia. Results obtained through a load census are compared with hourly consumption data collected via AMI. The analysis includes the construction of average load curves, heat maps, and variability metrics. Findings show that AMI, combined with data science tools, enables more accurate identification of consumption patterns and the generation of more robust inputs for energy efficiency decision-making. We further enhance this analysis by integrating uncertainty quantification (UQ) techniques, specifically focusing on quantifying the uncertainty associated with load forecasting.