A virtual model of data centre cooling

This study presents a calibrated, hybrid spreadsheet-based model developed to simulate the cooling energy consumption of a commercial-scale data centre in Dublin, Ireland. The model leverages five years of high-resolution, sub metered data, including chilled water flow rates, ambient conditions, and IT electrical load, offering a rare empirical foundation for system-level energy analysis. Existing modelling approaches often rely on simplified laboratory case studies, synthetic datasets, or isolated component analysis, limiting their relevance to operational facilities. This study introduces an innovative hybrid modelling framework that bridges the gap between black-box machine learning and rigid physics-only simulations. A key innovation is the use of a modular, Excel-based architecture that maintains high predictive fidelity (MAPE