Building Intelligent Positive Energy Districts

Positive clean Energy District’s (PED) are a key building block in the future energy paradigm for carbon-neutral cities and communities.

With the rise of modern technology, local digital twins – the digital representations of a functional territory combining low- and high-velocity data with dynamic models – play a significant role in PED development and the scaling of it, supporting decision makers and planners in taking informed decisions towards a sustainable future.

However, focusing narrowly on energy and mobility topics confined to the traditional sectors, digital twins for PEDs currently lack representation of significant aspects such as social, economic, and environmental properties, and hence, draw only part of the picture of a district or a city.

Limited by data availability and lacking awareness of existing data, this shortcoming in digital twin modelling for PEDs leads to suboptimal decisions, impacting negatively ambitious efforts of sustainable development in cities and communities.

This becomes even more clear when reflecting on the scalability issues across the 80.000 municipalities in the EU27: As highly complex entities, cities and communities differ in their physical, social, economic and even cultural structures, making it challenging to replicate PEDs in a trivial way across Europe.The BIPED project demonstrates how to overcome these barriers in a simple yet highly efficient manner that works everywhere by answering three key questions to push PEDs to the next level: wide deployment.Three key questions needs to be addressed to push PEDs to the next level:•How can digital twins be extended to refine a district’s profile representation, guiding PED design and demonstrators?•How can the quantitative collection of soft data support the advancement in digital twin development? •How to boost the replication potential of PED solutions for climate neutral cities with reinforced decision-makings