Automated Python workflow for climate resilience assessment of buildings under heatwaves and future climate scenarios using EnergyPlus.

This dataset contains a structured collection of Python scripts developed to automate the simulation, processing, and analysis of building performance under climate change scenarios. The scripts are part of the EDUPED research project and are designed to evaluate climate resilience in buildings through multiple dimensions, including energy demand, thermal comfort, and recovery capacity during extreme heat events.

The workflow integrates simulation outputs from DesignBuilder/EnergyPlus and processes them to compute resilience indicators such as Indoor Overheating Degree (IOD), Ambient Warming Degree (AWD), overheating escalation factor (α), absorptivity capacity, and recovery potential. The scripts also generate graphical outputs for comparative analysis across multiple passive strategies and climate scenarios (TMY2020, TMY2050 under RCP 8.5, and extreme heatwaves).

The dataset is intended to support reproducibility, transparency, and reuse of the methodological framework in building performance and climate resilience research.