SYMBIOTIC - Symbiotic Planning for Positive Energy Districts in Social and Subsidised Housing

The project develops a data-efficient and uncertainty-aware modelling framework to support municipalities in designing Positive Energy Districts (PEDs), particularly in contexts where data is limited or fragmented. By combining proxy-based data reconstruction, physics-informed energy modelling, and socio-economic analysis, the project enables a structured understanding of both the energy and social dynamics of urban areas at neighbourhood scale.

The framework integrates building and district-level energy modelling (heating, cooling, electricity), renewable generation, storage, and energy sharing, alongside modelling of vulnerability, affordability, and accessibility. This allows municipalities to assess current conditions and explore alternative intervention scenarios, ranging from short-term actions such as targeted retrofits to longer-term district transformation strategies.

A key innovation of the project lies in its ability to support decision-making under uncertainty, providing not only scenario outcomes but also an understanding of their reliability and associated risks. The modelling outputs are translated into planning-relevant insights through a scenario-based evaluation approach that considers trade-offs between energy performance, cost, and social impact.

The framework is implemented through an integrated research demonstrator that combines data, modelling, and scenario analysis into a coherent decision-support environment. This demonstrator is validated in real-world pilot contexts and designed to be replicable across different cities.

By enabling municipalities to make informed, data-driven decisions even in low-data environments, the project contributes to the development of inclusive, energy-efficient, and resilient urban districts aligned with European climate and social goals.