Local Digital Twins and Positive Energy Districts are fairly new concepts so it's not surprising they raise a lot of questions, especially when the two end up being part of a single solution. How do you even go about building an LDT for a PED? - we are often asked. While we can't give a definitive answer now - we still have 2.5 years to go before final results are produced - we are happy to share key outputs, insights and recommendations from an early experience of laying the foundation of a future LDT for a PED in Brabrand, Aarhus.
Technical architecture
Given the need to integrate multiple components that can function independently, are easily manageable and scalable, a modular structure has been adopted for BIPED’s architecture. In the LDT backend, the Core ingests and processes dynamic data (through the Open Urban Platform) and semi-static data (through the KPI Engine). The 3D model of a city comprising satellite imagery and building shapes is not funnelled through the Core to avoid unnecessary overload, and instead connects directly to the GIS publisher. The Core’s Model Coordinator provides the necessary data to the models and stores simulation results for later use. The models leverage multi-source data to forecast energy demand, simulate traffic what-if scenarios, perform environmental analysis, emotional mapping, and more. The Data Broker provides data and metadata in a coherent bundle using standardised data structures and programmatic interfaces. Finally, all the necessary user interfaces (3D map, dashboards, management view) are provided through the frontend to enable data exploration and analysis, as well as system management.
BIPED technical architecture
By structuring LDT in modular units, developers can isolate and address specific functionalities without impacting the entire twin. Concurrent development can proceed without undermining the ability to troubleshoot, upgrade and optimise individual components as necessary. Furthermore, modularity facilitates the integration of new features and technologies, making it possible for BIPED to adapt to evolving user requirements.
Modeling scenarios
Relevant datasets and variables for PEDs are those used to construct its energy profile (district heating, energy consumption), mobility profile (road network, traffic flows), socio-environmental profile (demographics, perceptions of happiness and safety, green spaces, weather) as well as the 3D model of a district (based on remote sensing data) . To ensure accuracy and adoption by local stakeholders, models are calibrated by aligning them with real-world measurements. In the next step, models are brought to bear in getting actionable insights to end users, with measures being controlled in user-specific front-ends. A key activity here revolves around what-if scenarios aimed at predicting system behaviour in response to specific interventions or unforeseen events.
BIPED LDT front-end in VC Map
Recommendations for success based on preliminary work
1) Establish a joint knowledge base between parties involved
Facilitate effective communication and knowledge sharing among all partners
Understand each partner’s capabilities and technical solutions
Document and disseminate the collective knowledge to support ongoing and future project phases
2) Achieve accurate data mapping and initial modelling
Conduct a thorough data mapping to understand data landscape and requirements
Develop initial data models that are accurate and align with the architectural design
3) Define basic technical requirements
Collect user requirements from potential adopters to develop epics
Collect technical requirements from solution providers to ensure a robust base for software architecture
Specify general software requirements
4) Design a robust LDT architecture (initial release)
Create a scalable and flexible architecture to serve as a foundation for LDT
Ensure the architecture supports integration with various data sources and technical components and models
5) Develop core technical components
Implement the essential technical components that will form the backbone of LDT
Ensure these components are modular and can be easily extended or modified
6) Integrate and align with parallel work streams
Incorporate stakeholder and end-user feedback into LDT design and implementation
Ensure LDT development is in sync with engagement activities and impact monitoring
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