NEEDs

Innovative Approaches for Energy Efficiency Improvement for Positive or Self-balanced Districts

The NEEDs project evaluates the integration of decision-making methods and machine learning to conduct thermo-, environmental-, and economic assessments of design and energy flexibility measures.

The methodology identifies scenarios with the lowest carbon footprint, minimized energy consumption and low costs while ensuring a comfortable and healthy indoor environment.

The project will develop innovative methods for optimization of solar panel installations, improve fault detection in district heating systems and conduct an analysis of the energy dynamics of hybrid photovoltaic and thermoelectric systems. Furthermore, advanced modelling techniques will be used to improve decision-making in energy efficiency improvements.

In addition, the project contributes to investigating stakeholders' experiences of positive energy districts and addressing the interplay between energy efficiency and user´s well-being in different urban contexts. The results are expected to contribute to promoting sustainable urban development and creating robust energy systems.