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Building Intelligent Positive Energy Districts

Periodic Reporting for period 1 - BIPED (Building Intelligent Positive Energy Districts)

Berichtszeitraum: 2024-01-01 bis 2025-06-30

Positive Energy Districts (PED) aim to produce an annual net-positive renewable energy balance. With the rise of modern technology, PED development is set to evolve towards a more agile arrangement in which decisions are first tested and fine-tuned in virtual environments before they are deployed on the ground. A key enabler of this virtual prototyping is the Local Digital Twin (LDT) technology. Traditionally, LDTs create digital representations of a functional territory by combining low- and high-velocity data with dynamic models of energy, traffic, buildings and natural environment. However, focusing narrowly on these domains means that digital twins of PEDs will lack representation of other elements that make up the urban fabric. LDTs that omit social, economic and cultural properties will only provide a partial representation of an area they are design to model. This shortcoming in LDT-PED modeling, which can be caused by limited data availability and siloed systems design, can lead to sub-optimal decisions, impacting negatively ambitious efforts of sustainable development in cities and communities. To address this challenge, a multi-dimensional LDT is being developed for the Brabrand district of Aarhus, Denmark. The tool, which can be used by urban planners and citizens alike, will ensure that the city can avail of the latest advanced technology to drive an ambitious district transformation toward climate neutrality, in a way that is green, digital, and people-centric.
The prototype of BIPED's digital twin is available at https://vcmap.bi-ped.eu/(öffnet in neuem Fenster). Users can browse the map in 3D and 2D. Three work-in-progress modules can be loaded to explore the solar potential of different rooftops in Aarhus (solar module), to view traffic flow simulations (traffic module), and to examine pollution levels (air quality module). Existing models and datasets are stored on the Civora platform (https://bi-ped.civora.org/app/home(öffnet in neuem Fenster)) which is continuously updated with new content. Future technical deliverables include the Load Forecasting Model, the Climate Risk Assessment Model, and the Indoor Climate Model.
BIPED is working to advance the State of the Art in the following three areas.

1) Extending LDT capabilities to better represent PED's multi-dimensional profile
Current LDT implementations lack sophistication necessary to characterise PEDs in all their complexity, as they typically address a limited number of urban systems, such as mobility, transport and energy consumption. BIPED will go beyond these domains to provide a deeper understanding of PEDs in general and Brabrand in particular. By integrating social, cultural and political properties of a city, BIPED will guide PED development toward a more holistic model that more accurately represents urban dynamics.

2) Enriching PED development by integrating 'soft' datasets
Properties that define a district's profile can often be measured quantitatively due to their discrete nature, using air or traffic sensors, for example. However, properties that are less quantitatively tangible, such as people's perceptions or urban environment, are harder to capture but, once tapped, can show whether and where citizens feel happy or sad. This kind of emotional mapping has huge, though as yet unexplored, potential for urban planning. BIPED will pioneer the development of novel methodologies for gathering such “soft data” and its adequate representation in LDTs.

3) Boosting PED's replication potential for the benefit of climate neutral cities
Although PEDs have common characteristics, they tend to be very specific to the local context. It is not easy to replicate the solution from one district to another, even in the same city, which limits the scalability potential. BIPED will use international standards, and in particular MIMs (Minimal Interoperability Mechanisms), to facilitate cross-district and cross-border integration of datasets, models and services. This will ensure that the necessary technical requirements are met to develop replication strategies on a country level as well as more widely across the Cities Mission.
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