Authors: Rushikesh Padsala, Volker Coors, Stuttgart Technical University of Applied Sciences – Hochschule für Technik (HFT) Stuttgart, Germany
1. Introduction: Moving toward Positive Energy Districts
How can urban planners, energy specialists, and local communities identify effective strategies to improve the energy performance of existing neighborhoods, where space for renewable energy installations is limited, buildings are aging, and energy demand remains high?
Transitioning existing urban districts toward sustainable, efficient, and flexible energy systems is a major challenge in Europe’s clean energy transition. Unlike newly developed districts, existing urban areas face constraints imposed by their established building stock, infrastructure, and urban layout. Identifying and assessing combinations of energy efficiency measures, energy flexibility strategies, and local renewable energy technologies is therefore essential for achieving Positive Energy District (PED) objectives.
Addressing these challenges has become increasingly important as Europe, guided by the vision of the Strategic Energy Technology (SET) Plan, aims to scale up PED-enabling solutions to at least 1000 districts with PED layers by 2040 and establish 100 Positive Energy Cities by 2050. According to the JPI Urban Europe framework, PEDs are energy-efficient and energy-flexible urban areas that aim to achieve net-zero greenhouse gas emissions and actively manage an annual local or regional surplus of renewable energy while interacting with wider energy, mobility, and ICT systems.
In Germany, Stuttgart’s Nordbahnhofviertel (Figure 1) provides a relevant case study district for exploring these challenges. Located next to the planned Rosensteinquartier, a major redevelopment associated with the Stuttgart 21 project, Nordbahnhofviertel is characterized by dense mixed-use development, an aging building stock (approximately 80% of buildings were constructed before 1990), and legacy energy infrastructure. While Rosensteinquartier offers opportunities to integrate modern energy systems from the outset, Nordbahnhofviertel faces the challenge of adapting its existing buildings and energy infrastructure to align with Stuttgart’s climate neutrality goals.
Within DigiTwins4PEDs, a European research project funded through the Driving Urban Transitions (DUT) Partnership, Stuttgart Technical University of Applied Sciences (Hochschule für Technik Stuttgart – HFT Stuttgart), in collaboration with its project partners and the City of Stuttgart, explored how Urban Digital Twins (UDTs) could support citizens and expert stakeholders in evaluating energy transition pathways and co-creating PEDs.
2. The challenge: Integrating Urban Energy Information for Early-stage PED Planning
Early-stage PED planning requires integrating information across multiple energy sectors, including building energy demand, heating and cooling systems, renewable energy generation, energy storage, and electric mobility. Beyond assessing annual energy balances, planners need to understand how energy demand and renewable generation vary throughout the day and across seasons to identify opportunities for improving energy flexibility, such as shifting household electricity consumption and electric vehicle charging to periods of high renewable energy availability.
However, integrating these heterogeneous urban energy data presents several challenges. Different energy modeling and simulation tools typically operate at different spatial and temporal resolutions and use different data structures and output formats. Furthermore, building-level simulation results need to be consistently aggregated to district-level and combined with information from other energy sectors. The lack of common data structures and standardized interfaces therefore makes exchanging, reusing, and combining simulation results across modeling tools and independently developed UDT applications difficult.
Beyond technical integration, planners, citizens, and other stakeholders need accessible ways to explore energy transition scenarios and make informed decisions. For example, what if more buildings adopted rooftop PV and households shifted electricity consumption and EV charging to periods of high renewable energy generation? What if annual building refurbishment rates increased, heating systems were replaced with heat pumps, and energy-efficient appliances became more widely adopted? Exploring such scenarios would help stakeholders assess potential benefits and trade-offs and support active participation in developing energy transition strategies for their district.
The Nordbahnhof case study therefore addressed these interconnected challenges by establishing an interoperable foundation for integrating multi-sector urban energy data across different spatial and temporal scales and enabling interactive, scenario-based exploration to support collaborative planning and citizen co-creation.
3. The approach: Building an interoperable UDT
To address the aforementioned challenges, DigiTwins4PEDs adopted an integrated approach combining two complementary components within a shared UDT environment (Figure 2): an OGC standards-based architecture for integrating and exchanging urban energy information, and a participatory framework enabling experts and non-experts to explore and discuss PED transition pathways. Together, these components connected technical energy assessments with stakeholder engagement to support early-stage PED planning.
The UDT architecture (Figure 3) comprises three layers: urban energy modeling and simulation, semantic spatial data infrastructure, and UDT applications. At its core, CityGML 2.0, an OGC standard for representing and exchanging 3D city models, provides the semantic city information model. Energy ADE 3.0 is a CityGML Application Domain Extension that adds concepts for representing cross-sector urban energy information across spatial and temporal scales. Its development is led by TU Delft for the conceptual data model, with HFT Stuttgart contributing to the Java library implementation. Together, CityGML and Energy ADE provide a common semantic basis for integrating urban energy simulation inputs and outputs independently of the modeling and simulation tools used. OGC-standardized web service and API interfaces, enable interoperable access to these data by UDT applications. This standards-based approach supports the reuse of urban energy data across different modeling and simulation tools and UDT implementations.
Energy ADE 3.0 is currently based on and extends CityGML 2.0, primarily due to its broader and more mature software support. However, its development already takes into account a future migration to CityGML 3.0.
For the Nordbahnhofviertel implementation, a CityGML 2.0 building model, including building functions and construction years, was provided in kind by the surveying department of the City of Stuttgart. CityDoctor was used for geometry and semantic quality management. Energy simulation was performed using SimStadt, EnergyPlus and Python-based models, while MAPED, developed by project partner AIT Austrian Institute of Technology, was used to assess Nordbahnhofviertel’s long-term PED potential. Simulation results were mapped to Energy ADE 3.0, encoded in XML, and stored in PostgreSQL using 3DCityDB. An OGC Web Feature Service (WFS) was implemented to provide energy attributes from Energy ADE to the UDT. CityGML building geometries were converted to 3D Tiles and served alongside terrain data using standard HTTP Apache server (OGC GeoVolumes API is also possible). Surrounding building geometries and the German topographic basemap were integrated through publicly available 3D Tiles and Web Map Service (WMS) from AdV (Working Committee of the Surveying Authorities of the Länder of the Federal Republic of Germany). Finally, the fronted UDT client, developed using CesiumJS (Figure 4), dynamically linked building geometries from 3D Tiles and WFS published Energy ADE attributes through their common gml:id identifiers.
4. From data to decisions: Supporting collaboration and co-creation
Building on the technical foundation described in the previous section, the Nordbahnhofviertel UDT was developed as an interactive decision-support application following a human-in-the-loop approach, enabling experts and non-expert stakeholders to jointly explore energy transition scenarios. The participatory sessions were embedded in Urban Living Labs (ULLs) which combined awareness-building activities followed by interactive scenario exploration using UDT, helping participants first develop an understanding of key energy concepts and then explore the potential implications of different energy-related decisions using the UDT.
To introduce key energy concepts, participants were engaged in gamified activities such as the Load Profile Demonstrator and LEGO Load Profile Game. For example, participants used LEGO bricks to construct daily household electricity profiles, illustrating how everyday activities influence energy demand. Such exercises helped establish a common understanding of energy system interactions before introducing UDT to the participants.
Following these activities, participants were introduced to the UDT through an interactive touch table (Figure 6). During moderated sessions conducted in collaboration with the City of Stuttgart, participants took on the role of district energy planners and explored different energy transition scenarios. The parametric UDT interface allowed participants to develop their own scenarios based on their preferences and priorities, while energy experts and city representatives facilitated the process and ensured the technical plausibility of the resulting scenarios.
The UDT enabled scenario exploration through interactive parametric sliders representing district-wide rooftop PV deployment, load shifting of appliances such as washing machines, dryers, and dishwashers, the adoption of energy-efficient appliances, EV penetration and charging flexibility, and annual building refurbishment rates combined with heat pump integration. Adjustments to these sliders triggered predefined WFS stored queries to retrieve relevant pre-simulated building-level energy information from the Energy ADE database. For example, the PV slider prioritized buildings with the highest rooftop PV potential, whereas the energy-efficient appliance slider identified residential buildings with the highest electricity demand for targeted energy efficiency interventions. The resulting energy profiles were aggregated at the district-level on the fly and compared against baseline profiles, allowing alternative scenarios to be evaluated without rerunning the underlying simulations. The results were presented through interactive visualizations and key performance indicators (KPIs), including annual net energy balance, electricity self-consumption and self-sufficiency, hourly peak loads, PV coverage of electricity demand, grid imports, surplus PV generation, estimated electricity cost savings and potential reductions in space heating demand due to building refurbishment. The scenario sliders were also synchronized with the interactive 3D district map, which highlighted the buildings selected for each intervention, allowing participants to visualize the spatial distribution of scenario measures alongside their energy impacts. Together, these KPIs and spatial visualization helped participants understand the relationships between different energy interventions and their combined effects. For example, increasing rooftop PV installation in the district did not necessarily mean that all generated electricity could be consumed locally, while shifting appliance usage and, where possible, EV charging toward periods of higher solar generation could improve the district’s local self-consumption and energy self-sufficiency.
5. Outcomes and lessons learned
The Nordbahnhofviertel case study demonstrated how heterogeneous urban energy information could be integrated using standardized semantic data models and OGC web service interfaces to support interactive district-level energy planning. Beyond technical integration, the UDT provided a shared environment connecting energy assessments with participatory energy planning. Its KPIs and visualizations supported iterative discussions between citizens, energy experts, and municipal planners, allowing local preferences to be considered alongside simulated energy impacts. These discussions also revealed practical barriers not fully captured by the technical assessments, including affordability, building ownership, and heritage restrictions. Combining these local perspectives with the scenario results provided energy experts and municipal planners with insights that could inform the setting of realistic, socially informed district energy targets, as well as the development of supporting policies and incentive measures. For citizens, this approach provided an opportunity to actively engage in energy planning and make more informed contributions to shaping their district’s energy future.
Beyond Stuttgart, the UDT architecture was transferred to case study districts in Vienna, Rotterdam, and Wroclaw using a UDT client developed by InfoSolutions (Figure 7) – our project partners from industry/private sector. Unlike Nordbahnhofviertel, where simulation-ready CityGML data were provided by the City of Stuttgart, the other case studies required varying degrees of data preparation and enrichment, including the reconstruction of a CityGML Level of Detail 2 (LOD2) building model in Wroclaw. Nevertheless, the underlying CityGML and Energy ADE semantic models and OGC web service interfaces were reused without changes to their schemas or service designs. This provided initial evidence of the architecture’s interoperability across different urban contexts and independently developed UDT applications.
The cross-city implementations also highlighted the importance of data availability and quality for developing interoperable UDTs. For cities pursuing similar approaches, geometrically and semantically validated and simulation-ready 3D city models with essential building attributes, particularly building function and year of construction, are important prerequisites. Consistent building identifiers across municipal datasets are essential for facilitating easier data integration. Furthermore, incorporating energy-related information into CityGML models using semantic extensions such as Energy ADE 3.0, at appropriate spatial scales ranging from individual buildings and building blocks to larger areas such as districts through the Urban Function Area module, could reduce repeated data preparation and facilitate data reuse across modeling tools and UDT applications.
6. Conclusion: What other cities can take away
The Nordbahnhofviertel case study illustrates how interoperable UDTs can bring together urban energy information, scenario assessments, and citizen participation in a shared digital environment, making complex energy information accessible to citizens and incorporating their perspectives into district energy planning during early planning stages. The transfer of the standards-based architecture to other European cities further demonstrates its potential for reuse in different urban contexts.
The key takeaway is that open geospatial standards provide a reusable foundation for integrating and exchanging urban energy information, while UDTs turn this information into shared decision-support environments where citizens, energy experts, and municipal planners can collaboratively explore pathways toward PEDs and advance the clean energy transition goals of cities.
Acknowledgments
The authors would like to thank Dr. Giorgio Agugiaro (TU Delft), Amando Reber (HFT Stuttgart), Jędrzej Zielonka and Stanisław Biernat (InfoSolutions), Simon Lempp and Lea Koch (City of Stuttgart) and the entire DigiTwins4PEDs project team for their continued help and support. The authors would also like to thank the City Surveying Office of Stuttgart (Stadtmessungsamt Stuttgart) for kindly providing the CityGML building models of the Nordbahnhof district used in this study. The work presented in this article was funded by the German Federal Ministry for Economic Affairs and Energy (BMWE) for the research project DigiTwins4PEDs (case study: Stuttgart) as part of the ‘’Driving Urban Transitions’’ partnership, which was co-financed by the European Commission (Grant Number: 03EN3081A). Overall, DigiTwins4PED project has been funded by partners of the DUT Partnership through the Joint Call 2022. As such, this project has received funding from the European Union’s Horizon Europe research and innovation programme under the grant agreement no. 101069506.
