As negative effects of climate change become increasingly prevalent, carbon emission reduction has become the need of the hour. To meet carbon reduction goals, municipalities, universities and organizations with large real estate portfolios need reliable and adaptable models that provide detailed building performance metrics to efficiently manage future energy demand. However, creating calibrated energy models at the multi-building scale is often a time-consuming task. This project investigates methodologies to partially automate the buildup and calibration of energy models for the authors´ home institution. The project explores a workflow that uses UAV photogrammetry and mesh manipulation to automate 3D model generation, metered energy data and quick surveys as inputs to generate multi-zone EnergyPlus building energy models that are then calibrated using parameter screening and optimization. The calibrated models are used to assess energy performance under the projected climate in the future and evaluate retrofitting scenarios.