Cities across Europe are working toward cleaner, more efficient energy use—and one promising concept is the Positive Energy District (PED). The EXPEDite project is helping turn this idea into reality by using advanced digital twins—virtual models of real neighborhoods—to better understand and manage energy use.

At its core, EXPEDite gives city planners and local stakeholders tools to monitor energy production, balance demand, and make smarter decisions at the neighborhood level. But there’s a challenge: many of these technologies rely on expensive data and specialized equipment. This creates a gap between well-funded cities and regions with fewer resources.

To bridge that gap, EXPEDite focuses on affordable, scalable solutions. Instead of relying on costly proprietary data, the project uses open-source information and widely available tools. The goal is simple: make digital twin technology accessible to more communities, while ensuring it remains legally compliant.

A Closer Look: The Athens Pilot

A recent study from ExPEDite partners to replicate parts of the ExPEDite solutions in Riga (LT) to Athens (GR) demonstrates how this approach works in practice. Soon to be published as a book chapter titled “From 3D Data to Sustainable Governance: A Scalable, High-Fidelity Digital Twin for Urban Energy Management” (IntechOpen, 2026), the research outlines a practical method for building detailed digital twins at low cost.

The team tackled a common issue known as the “BIM-GIS silo”—where architectural data and geographic data don’t easily work together. Their solution combines open data sources like national cadastral portals, Google Earth Pro, and Street-view imagery to generate high-fidelity Building Information Models (BIM). These models are georeferenced to the Greek Grid (EGSA 87′) and transformed into the WGS 84 coordinate system for accurate global synchronization via the Cesium for Unreal plugin.

These models are then integrated into a powerful simulation environment using a real-time engine (hosted within Unreal Engine 5 (UE5), utilizing Nanite virtualized geometry and Lumen global illumination) , allowing researchers to analyze things like solar energy potential and building shadows across entire neighborhoods.

Smarter Energy Insights

The Athens digital twin also includes high-frequency energy data, collected every 10 seconds. This allows for Non-Intrusive Load Monitoring (NILM), a method that breaks down total energy use into individual appliances—without installing sensors everywhere.

This level of detail helps identify where energy can be saved, especially during peak demand times, enabling more targeted and effective interventions.

Ensuring Legal and Ethical Compliance

Beyond technical innovation, the project also addresses legal challenges. Using the CadaSPACE approach, property rights are modeled in 3D rather than flat 2D maps. This ensures that any automated decisions or predictions respect building regulations, ownership boundaries, and privacy laws such as GDPR.

Key Takeaways

The Athens replication pilot shows that:

• High-quality digital twins can be built affordably using open data
• Real-time simulation tools can support large-scale urban energy analysis
• Detailed energy insights can be achieved without intrusive hardware
• 3D property modeling is essential for legal transparency and compliance

Looking Ahead

This research will appear in the upcoming IntechOpen volume “Geographic Information Systems – Analysis Tools, Predictive Analytics, Geospatial AI, and Dynamic Modeling” (2026). It highlights a clear message: smart city technologies don’t have to be expensive or exclusive. With the right approach, they can be scalable, accessible, and ready to support sustainable urban futures everywhere.