Data-driven characterization of cooling needs in a portfolio of co-located commercial buildings

The increasing cooling needs in commercial buildings, exacerbated by climate change, warrant immediate attention. These buildings, characterized by their long lifespans and slow stock turnover, change consumption over time. This study develops simple, interpretable data-driven models using weather- and occupancy-related features to analyze the cooling in different types of co-located buildings. Over five years, our models effectively predict the cooling load across buildings with R-squared values of 81%-87%. Factoring out geography-driven differences, we identify strong heterogeneity within and across different buildings. The average estimated base load cooling varies between 0.50 and 4.4 MJ/m