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 was successfully presented during the significant scientific event in the area of modern Housing research: the conference IAHS 2018, which has been held in Naples, Italy, between 10th and 13th of April.

This is one of most important conferences for scientific Housing society representing academic and research institutions from all over the world. International Association of Housing Science (IAHS, based on Florida's University of the World) is regurarly the host of the conference gathering experts and professionals from various research centers.

Dawid KrysiƄski, PhD, an expert of ASM - Market Research and Analysis Center (project partner) gave the lecture entitled: "Innovative business models for deep residential renovation processes with demand response schemes", strictly connected with the idea of solutions to be elaborated within the MOEEBIUS project structure. The lecturer put the emphasis to the aspect of the possible way to market of the ultimate project product and to business models assuring the benefits to end-users of project solutions.

The motto of this year's edition of IAHS Housing Research conference is: "The housing for the dignity of mankind". So the congress is an ideal forum to disseminate recent advances and discuss future trends towards a more sustainable, innovative and accessible construction industry.

 

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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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