Fraunhofer Institute for Building Physics IBP
Fraunhofer Institute for Building Physics IBP

Urban Digital Twin for Positive-Energy District Design: Cooperation Between Fraunhofer IBP and Concordia University in Canada

Planning Positive-Energy Districts (PEDs) is vital for the urban energy transition, yet current tools force a compromise between simulation speed and crucial environmental detail. Project CIPED (Climate-Informed PED Design)—a joint initiative between Concordia University and Fraunhofer IBP—solves this with a rapid, AI-based Urban Digital Twin. By merging district-wide energy models with high-resolution microclimate simulations, CIPED overcomes traditional bottlenecks. Leveraging advanced Deep Learning, this simulation engine will integrate into IBP’s OASITY® platform. It empowers urban planners and decision-makers to optimize renewable energy matching, combat urban heat, and design climate-resilient cities faster and more accurately than ever before.

Project goals

  • Develop an Urban Digital Twin: Create a rapid, AI-based simulation platform to virtually prototype Positive-Energy District designs and retrofits.
  • Bridge Modeling Gaps: Merge macro-level Building Energy Models with high-resolution Urban Canopy Models for localized microclimate simulations.
  • Accelerate Simulation: Drastically reduce computation times using a novel Deep Learning pipeline, outperforming traditional physics-based models.
  • Optimize Urban Planning: Empower stakeholders to efficiently match energy demand with renewable generation, implement heat mitigation strategies, and reduce carbon footprints.
  • Overcome Technical Hurdles: Solve complex challenges like downscaling mesoscale weather data and managing massive datasets via High-Performance Computing.
  • Future-Proof Operations: Evolve (beyond current project) into a live operational engine utilizing AI forecasting for real-time Demand Response, Load Shifting, and Vehicle-to-Grid balancing.

Project status

First deliverables are expected by end 2026 and include historical urbanized WRF simulations and future CORDEX projections for reference weather stations as well as static and dynamic input data for the PALM-4U microclimate model.