This building performance dataset provides two years of hourly hot-water meter readings for non-residential building assets in CSV. The dataset contains two years of hourly whole-building hot-water meter readings specifically curated for non-residential structures. It provides structured time-series data that allows for the analysis of thermal energy consumption patterns across diverse building typologies. The CSV files are formatted to ensure compatibility with standard data science workflows, enabling seamless integration with other meter and weather series data. This collection serves as a foundational resource for researchers and engineers aiming to benchmark operational energy performance, identify usage anomalies, and refine predictive models for hot-water demand in complex commercial and institutional environments.

The download is a single file containing .CSV files.

Professionals can integrate this dataset into Python, R, or Excel environments to perform statistical analysis or machine learning tasks. The data is structured for time-series alignment, allowing users to cross-reference hot-water consumption with external variables like weather data or occupancy schedules. By loading these CSV files into data processing pipelines, practitioners can develop custom energy models, train neural networks, or validate building performance simulations against empirical, real-world operational consumption profiles.

This dataset is essential for MEP engineers, sustainability consultants, and building scientists engaged in energy auditing and performance optimization. It is particularly valuable for projects involving commercial office blocks, hospitality venues, and institutional buildings where hot-water demand significantly impacts total energy loads. Use this data to calibrate energy simulation software, perform longitudinal usage studies, or develop effective demand-side management strategies. It serves as a reliable benchmark for evaluating the efficiency of domestic hot-water systems in large-scale non-residential developments.