Urban sustainability

Innovative simulation tools

Real-life models

Modelling Optimization of Energy Efficiency in Buildings for Urban Sustainability

MOEEBIUS introduces a Holistic Energy Performance Optimization Framework that enhances current modelling approaches and delivers innovative simulation tools which deeply grasp and describe real-life building operation complexities in accurate simulation predictions that significantly reduce the “performance gap” and enhance multi-fold, continuous optimization of building energy performance as a means to further mitigate and reduce the identified “performance gap” in real-time or through retrofitting.

 

MOEEBIUS project has been presented on Sustainable Places 2018 conference and valued as one of most significant and unique initiatives helping to reduce gap between predicted and actual energy performances at the level of buildings and blocks of buildings.

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Dawid KrysiƄski, PhD, an expert of ASM (MOEEBIUS Partner), presented the structure, main objectives and current achievements of the project. The workshop focused on presentation of projects similiar to each other was organized within the framework of conference to help the participants to understand the remaining barriers and opportunities in reducing the energy performance gap, while examining the requirements of energy management business models and the roles of both citizens and data management.

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Sustainable Places is one of the most significant, European scientific conferences in the field of modern buildings and construction research. Once a year it gathers stakeholders from leading organizations around the world to advance the state of art and play role in one of the greatest challenges that our societies and their urban planners have ever faced: The need to enhance the sustainability of places ensuring long-term environmental security.  

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Saturday, August 18, 2018

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EU  This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 680517.

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