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.

 

The whole Consortium of MOEEBIUS gathered in beautiful, picturesque venue of Vila Gale Hotel in Ericeira, Portugal, to participate the 7th General Assembly of the project. This is the time of conclusions since the project's life is slowly coming to its end (April 2019), so MOEEBIUS experts are mainly focused on results and progress of specific work packages and on remaining work programme.

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The assembly is planned for three days: 20 - 22 of November. Yesterday the entire conference day was dedicated to discussions related to work carried out and results achieved in the frame of technical work packages: WP6 (MOEEBIUS Decision Support System for Holistic Energy Performance Optimization) and WP7 (Pilot Setup and Validation). Today discussion is continued in the area of technical topics (Use-case applications on the pilot sites) but, subsequently, the Consortium is going to analyse project's Exploitation Plan with Market Intelligence Activities - and also to focus on MOEEBIUS current dissemination activities, including the schedule of project's final conference which is planned for the end of February next year in the framework of World Sustainable Energy Days 2019.

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Tomorrow, during the last day of General Assembly, meeting participants are going to visit Mafra City hall and Venda do Pinheiro school and kindergarten: pilot site's buildings of MOEEBIUS project.

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Sunday, December 16, 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.