Urban energy planning relies on digital technologies to support the transition toward more sustainable cities. In this context, Urban Digital Twins (UDTs) are emerging as key tools to manage, visualize, and analyse complex urban data. Many scholars have highlighted the potential of UDTs in energy simulation fields, namely positive energy districts (Coors and Padsala, 2024), household consumption (Padsala et al., 2024), heating demand (Würstle et al., 2020), and greenhouse gas emissions (Alva et al., 2024), across various scales.

This work aligns with the current discourse around developing Energy UDTs by ensuring a direct coupling between an UDT platform (City2Twin) and a Building Energy Simulation (BES) model. This integration generates detailed energy data and enriches 3D city models with domain-specific attributes such as heating demand, supporting decisions related to urban heating and retrofitting planning. The approach uses the geometric data from the UDT to feed an automated, parametric energy model and reinjects the simulation results into the UDT for visualization and analysis.

Most urban-scale energy assessment tools rely on archetypes, degree-day methods, or benchmark data, which often overlook individual building characteristics such as geometry, thermal inertia, or usage patterns. In contrast, this method applies a more detailed, data-based simulation while remaining computationally efficient. This coupling offers a scalable, standardized, and data-driven solution that bridges the gap between digital urban models and building-level thermal simulations. Reintegration into the UDT improves the structuring, accessibility, and interpretation of energy data for planning and policymaking. The workflow is tested on a real urban district to assess its feasibility and potential for broader application.