Uncertainty from Model Calibration: Applying a New Method to Transport Energy Demand Modelling

Uncertainties in energy demand modelling originate from both limited understanding of the real-world system and a lack of data for model development, calibration and validation. These uncertainties allow for the development of different models, but also leave room for different calibrations of a single model. Here, an automated model calibration...

Urban building energy modeling using a 3D city model and minimizing uncertainty through Bayesian inference: A case study focuses on Amsterdam residential heating demand simulation

To cut down immense greenhouse gases emission and energy consumption in the rapidly urbanizing world, a holistic understanding and rethinking of our dynamic urban energy system are inevitable. Performing bottom-up building energy modelings at urban scale based on Geographic Information System (GIS) and semantic 3D city models could be a...